Analysis of Wind Turbines Blockage on Doppler Weather Radar Beams

INTRODUCTION

Partial blockage of radar beams by any natural or man-made obstacle results in a deterioration of the radar performance and loss of sensitivity to atmospheric precipitation and wind conditions. In this respect, due to its high-level radar cross sections and the rotation of its blades, wind turbines have potentially strong impact radar capacities. In many locations, the growing number of wind turbines close to those geographical elevated spots until now only occupied by radars is becoming a serious threat to the reliability of radar meteorological measurements.

Wind turbines can impact coherent radars if they are within the radar’s line of sight [1].Within a few kilometers from the radar, they are close enough to partially block a significant percentage of the beam and attenuate signal downrange of the wind turbine. They can also reflect energy back to radar and appear as clutter on the radar image and contaminate the base reflectivity data [2], [3]. Finally, if the turbine blades are moving, they can impact the velocity and spectrum width data [4].To analyze the effects of wind turbines blockage on coherent weather radar performance in a realistic way, it is necessary to consider the use of simulations of beam propagation in three-dimensional media. This study shows the viability of the split step solution to simulate the propagation phenomena.

PROPAGATION AND ANALYSIS TECHNIQUE

The parabolic approximation to the wave equation and its split-step solution [5] has been used extensively in a variety of context to simulate propagation phenomena in both deterministic and random media (e.g., [6]–[8]). The split-step method offers a numerically efficient, full-wave solution to the field because of the implementation of discrete Fourier algorithms in a computer model.

Physically, the split-step technique corresponds to dividing the medium into slabs, each of which introduces a spatially varying contribution to the phase defined by the atmospheric refraction in the slab, and the radar wave beam is then propagated through a uniform medium from screen to screen. Although wave front bends and radar beams are normally refracted downward toward the Earth, a curvature transformation is made that effectively maps the range-dependent terrain coordinate system to a flat or smooth earth coordinate system.

In this analysis a more point-like source with significant angular spread is required. This effect may be modeled by propagating in spherical coordinates. This approach, where the propagation medium is divided into spherical shells, keeps angular resolution constant. It allows us high resolution near the source and decreasing resolution with increasing sampling interval as the propagation distance increases. The electric field envelope U(r,R) characterizes the radar beam considered in this study, which is assumed to be varying relatively slowly in range R. If Un is the solution at range Rn, by using the split-step technique to the parabolic wave equation, the solution Un+1 at range Rn+∆R can be approximated analytically in terms of Un with a second-order accuracy by the symmetric split operator

Un+1=exp (− j ∆ R

4 k∆⊥2¿ exp (-jkN) * exp (

− j ∆ R4 k

∆⊥2¿Un

Where ∆⊥ is the transverse part of the Laplacian operator. This solution allows us to apply a numerical scheme in which the field has to be propagated twice a distance ∆R/2 in free space by using the operator

SF= exp (− j ∆ R

4 k∆⊥2¿

and the medium has been reduced to a series of independent phase screens defined by

SP= exp (-jkN)

Here, N reflects effect of the medium refractive index. When the radar beam encounters an obstacle, i.e., terrain and wind turbines, power are removed from the beam and a radio shadow appears behind the obstacle. The effect is readily simulated by defining a numerical mask that collocated with the medium phase screen; properly blocks the propagation field Un at the right transversal coordinates r. This occultation effect builds up by diffraction over many consequent slabs and produces wave field distortions.

The three operators defining solution (1) are applied sequentially so that it can be solved separately. The free-space propagation operator (2) can be expressed in Fourier transform space as a simple phase change

u (K, Rn +∆ R2

)=exp [jk(1

2 R n− 1

2 R n+∆ R¿∨K∨2¿u (K , R n)

where u(K,R) is the Fourier transform of the electric field envelope U(r,R). Using the fast Fourier transform (FFT) allows numerical propagation of the field from screen to screen in a very efficient way.

CONCLUSION

The technique divides the medium into slabs, each of which introduces a spatially varying contribution to the phase defined by the atmospheric refraction, and the radar waveform is then propagated through a uniform medium from screen to screen. When the radar beam encounters terrain and wind turbines, occultation effect builds up by diffraction over many slabs and produces a complex radiation lobe structure. The large number of spurious radiation lobes in the turbine-modified antenna radiation pattern may challenge the accuracy of radar measurements.

From our analysis, it results clear that wind turbines within 3 km of meteorological radars can prevent the radar’s beam from correctly shaping and cause considerable radar estimation errors down range from the turbines.

Application of the Radar Cross Section RCS for Objects on theGround - Example of Wind Turbines

ABSTRACT

Wind turbines are often to be located in some distance to ground based navigation, landing and radar systems. The minimum actual permissible distance to the system has to be determined in some way – often done by the RCS scheme for radar system. RCS is not defined for objects on the ground if the ground is relevantly illuminated by the radar in a practically realistic finite distance. The ground as well as the near-field effect and the highly statistical behavior of the RCS in space and time for realistic distances prevent a reasonable determination and application of the RCS.

INTRODUCTION

Wind turbines are installed in a rapidly increasing number in some distance to navigation and/or radar systems which are the focus of this paper. By that, there is a principal and classical conflict between the assigned specified task and mission of the radar and the installation of the turbines for the sake of renewable energy which has an increasing priority in the countries and societies worldwide.

Figure 1 : Wind turbine in the radiation field of a radar above ground in some distance D.

The easiest way if possible seems to be to install the turbines (sufficiently) far away. To determine this crucial distance the RCS (Radar Cross Section) is used by radar operators.

RADAR, RCS AND WIND TURBINES

The Radar Cross Section RCS is a widely used classical scheme to characterize a target for radar for the determination of the range and visibility. The RCS (σ, radar cross section; monostatic, bi-static) is defined for a plane wave excitation [1]. It is a useful parameter for objects of limited size in space such as the aircraft or other flying objects (high) above ground. The general definition of the RCS (1) [1] assumes an asymptotic infinite distance.

σ =limR

→ ∞¿R2¿ E p s∨2¿E q i∨2

¿

This well known formula contains the obligatory limit condition R→∞ which implies a plane wave excitation. The plane wave is characterized by constant amplitude and by a linearly progressing phase across the object. A single harmonic frequency is also assumed implicitly and, by that, Doppler shifted back-scattering spectrum [6] is not covered by the RCS-scheme.

Wind turbines are large mechanically and electrically very large complex objects having also large rotating blade structures. Besides the basic condition of the plane wave which is not met generally due to the ground interaction, the next problem in the applied RCS is related to the scattering properties of an

object in finite distances, i.e. near-field effects. The RCS is defined for a plane wave which may be approximated by far-field conditions.

However, the well known far-field distance DF=2d2/λ is excessively large for the wind turbines. One has to realize that the far-field distance depends on both dimensions, of the radar antenna as well as of the electrical size of the object. One can conclude that far-field distances can never be achieved practically in the field.

RADAR SYSTEM EFFECTS OF TURBINES AND RCS

Some typical and not complete effects of the turbines are Shadowing and range reduction. Field recovers faster for larger distances of the radar. Backscatter clutter mono-static and Doppler shifted spectrum. Static clutter will be suppressed in

the radar MTI/MTD signal-processing. Bistatic scattering in case of secondary surveillance radar. False interrogations or ghost targets or

tracks (primary and secondary radar) cannot be analyzed by the standard mono-static RCS in general.

SUMMARY AND CONCLUSION

It has been shown again by basic theoretical facts that the calculated or measured RCS according to the standard definition is not applicable by fundamental theoretical reasons. Each safeguarding scheme on the basis of the RCS is by that arbitrary. Safeguarding distances are easily exaggerated depending on which RCS-figure is assigned and processed. The real scattering system analysis is the solution for a realistic treatment.

DESIGN AND REALISATION OF ACTIVE COATINGS FOR WINDTURBINE BLADES

Concerns about global warming and the consequent search for greener methods of power generation, there is considerable interest in identifying techniques for ameliorating the reflection of radar signals from wind turbine generators as these can lead to problems with radar systems due to target masking, increased clutter and false tracks due to blade-induced Doppler effects. Design and realization of active coatings which might either counteract Doppler signals due to blade rotation or which might provide a means of labeling particular radar returns from wind farms so that they might be rejected in the radar signal processing.

Phase switched screen (PSS is a surface which does not attempt to suppress the reflection of incident radar signals, imparts binary phase modulation to the reflected signal so as to alter its spectral characteristics. Hence the reflected signal may either still fall within the receiver pass band but have user-specified Doppler characteristics or it may resemble a spread spectrum signal and thus not be detectable by the radar receiver [1], [2].

Detection and mitigation of wind turbine clutter in C-band meteorological radar

ABSTRACT

Wind farm installations that are near radar systems cause clutter returns that can affect the normal operation of the radar. Wind turbines provoke clutter reflectivity returns with unpredictable Doppler spreads that are not easily minimized. The proposed detection technique is applicable when using the spotlight operation mode during radar data gathering. This means that the dwell time must be long enough to observe certain statistics that allow for the detection of wind turbines. The detection technique can be applied before or after real rain data are added to WTC, with different results.

INTRODUCTION

The use of wind farms to generate electricity is growing because of the importance of renewable energy sources. These installations can include more than a hundred turbines as tall as 120 m. Moreover, windmills are expected to be significantly higher in a few years. This continued growth is seriously threatening the performance of most radar systems [1].

Because of their large radar cross section (RCS) – as much as 1000 m2 in some instances [3] – wind farms are easily detected by radar. As a consequence of the rapid rotation of the blades, conventional clutter filtering is useless. For example, the Gaussian model adaptive processing (GMAP) algorithm [4] implemented does not help because it only removes the ground clutters zero velocity components. This algorithm supposes a Gaussian shape of the rain spectrum to calculate how many points near zero velocity are removed.

A typical wind turbine is made up of three main components: the tower, the nacelle and the rotor. The tower generates a constant zero velocity return that is easily minimized with appropriate Doppler processing, such as GMAP. Unlike the tower, the turbine nacelle RCS is a function of the turbine yaw angle, which affects the radar signature. Moreover, most wind turbines have curved surface nacelles that scatter the energy in all directions, which increases the variability of the RCS.

The rotor allows the blades to move fast enough that they are not suppressed by stationary clutter filtering. In fact, we can easily observe blade tip velocities of up to 90 m/s, which exceed the maximum non-ambiguous velocity programmed into most weather radar systems. Typical parameters are shown in Table 1.

Table 1: Typical Wind Turbine ParametersModel G-58 G-86 G-90Power ,kW 580 2000 2000Blade Length ,m 28.3 40.5 44Tower height ,m 44-71 67-78 67-100Rotation ,rpm 15-31 9-19 9-19Max.tip speed ,m/s 91 80.5 87.5

Another point to consider is that the layout and spacing of the wind turbines within the wind farm will also affect the manner in which the radar is impacted. This separation is typically on the order of a few hundred meters, comparable to contemporary weather radar range resolution. Depending on the location and layout of the wind farm, weather radar may or may not resolve the turbines. If the spacing between two wind turbines is smaller than or equal to the cross range and down range resolution, the radar will not resolve the two turbines and they will appear as one large target. A priori, for mitigation purposes, it is preferable to have larger spacing between wind turbines.

A few ways to mitigate the effects of wind turbine clutter have been studied. Wind turbines cause several types of distortions to radar.

First, the shadowing caused by wind farms can result in precipitation detection errors. This is important only if the distance from the radar is less than 5 km [5]. Second, the stationary parts of wind turbines generate clutter signals. The GMAP algorithm will reduce this effect, but if the return is very powerful, it can saturate the receptor. Third, and most important, the backscattered signals of the blades create Doppler frequency shifts that can be spread across the frequency spectrum. This creates wind speed errors as well as false reflectivity returns. These distortions may cause the meteorological algorithms to fail and may give false radar estimates of precipitation accumulation, false radar Signature and incorrect storm cell identification.

The contributions from different parts of a blade are coherent only when the blade is perpendicular to the line of sight. If there is no perpendicularity, the vector sum is destructive because of the variability of the phase. In the blade tip alone, the vectors are insufficient to cancel out the signal and a peak appears. Because the blade trajectory describes a circle, a sinusoidal function is apparent in the data (simple harmonic movement). Negative Doppler shifts, that is, blades going down, are less powerful because of differences in the RCS between blade sides. This may also be linked with possible shadowing of the radar beam.

However, in most cases the yaw angle is not very helpful, and the blade’s energy returns, namely, the flashes, are widely spread over the Doppler frequency spectrum, and there is significant ambiguity. We note that the maximum non-ambiguous velocity for operational mode of the radar is only 18 m/s, whereas blade tip velocities can reach 90 m/s for this type of turbine

Certain mitigation schemes have been developed for spotlight operation, with the aim of removing or minimizing the flashes produced by the blades. The work presented by Gallardo-Hernando et al. [11] introduced a novel method for removing the flashes without distorting the information between them. The Radon transform was employed to isolate flashes in the new image domain, so that all of the flashes could be suppressed. The radon transform of an image is calculated by integrating the intensity values among straight lines characterized by an angle and a distance. Therefore the vertical lines in the original image are going to be seen as 00 points in the radon domain. The inverse transformation subsequently returned a corrected image that contained the weather information alone. However, the higher level of noise outside the flashes continued to impact the weather information. In addition, the computational cost was too high to allow real-time operation.

DETECTION OF WTC IN SPOTLIGHT MODE

The detection of clutter is based on the periodic features of the signals [12].Dwell time must be sufficient to observe, theoretically, at least two flashes. The peaks in the signal correspond to backscattering in the three blades. By calculating the power spectrum of the time series for each range bin, we can find any periodic signal and thereby estimate the rotation rate of the blades.

To summaries, the algorithm would follow three steps for each range bin: (i) estimate the power spectrum, (ii) compare its maximum value with an appropriate threshold and (iii) check whether the resulting rotation rate is within the range of Table 1.

SIMULTANEOUS DETECTION AND MITIGATION

Wind farms are composed of dozens of wind turbines. These turbines can move independently; therefore, the clutter produced by the wind farm is constantly changing. Different shadowing effects appear, and different velocities will be apparent. Moreover, atmospheric conditions can also affect the manner in which the radar detects the wind farm.

Given this, it is also necessary to design adaptive detection schemes. In other words, WTC must be detected in each exploration, immediately before mitigation.

CONCLUSION

This paper has focused on how wind farms disturb the performance of C-band weather radars in two main ways. First, they cause an overestimation of rain reflectivity because of the large RCS of wind turbines. Second, they cause errors in wind velocity estimation because of the fast blade rotation, which produces very wide, or even ambiguous, Doppler spreads.

We conclude that these effects can be minimized with appropriate processing. In the case of spotlight operation mode, WTC can be easily detected by studying signal periodicity, as we have proved. The WTC mitigation protocol must guarantee the continuity of all weather information. The decision to use fixed or adapted WTC detection methods has to be made consistent with the general behavior of real-world wind farms. The developed algorithm is based on spectral estimation and makes use of amplitude and velocity thresholds. Our detection techniques can be used to develop a precise clutter map that could be used in the future with every radar operational mode. The implementation of this algorithm in an operational environment requires the antenna radar to be stopped. In ordinary weather radar this can be done between radar exploration scans.

Effects of wind power plants on passive radar operation

INTRODUCTION

Today, wind power plants are becoming more common in off shore as well as in midland locations. They can influence the detection performance of radar systems, in particular with respect to low flying targets. Since such wind power plants are generally installed on elevated terrain in order to best profit from wind currents, they virtually increase the horizon level and thus can limit the line-of-sight range.

TARGET SHADOWING BY WIND TURBINES

With mast structures of 60 m and more and rotor diameters of 30 to 40 m wind turbines can obstruct the radar line of sight and disturb radar detections by masking, in particular due to the relatively large structure of the turbine shelter. At lower frequencies (VHF/UHF), however, which are potential illumination frequencies for passive radar, the effect of masking is alleviated by diffraction propagation at the edges of obstacles like such turbine shelters. Furthermore, since passive radar exploits bi- or multi-

static geometries, masking may only occur on one of the propagation paths, transmitter-target or target-receiver and profit can be taken from multiple illuminations.

Thus, not negligible masking is primarily expected from large wind mill parks, which stretch in two dimensions. In addition to possible masking effects wind mill turbine shelters can produce strong stationary target returns (Clutter), since their dimensions are in the order of magnitude of the wavelength and resonance effects are likely to occur.

SCATTERING OF ROTOR BLADES

Scattering of illuminator signals at the rotating rotor blades is observed, too, if the blades are made of or contain conducting material. This is generally the case since lightning protection rods are implemented in the rotor blades and often carbon fibre material is used.

The current generation of wind mills primarily features 3-blade rotors with synchronous or asynchronous machines which allow variable rotation rates. Reflections from the rotor blades are periodical and show a Doppler shift, which is dependent on the rotation rate, the rotor diameter and the bistatic geometry. So called blade flashes are observed, whenever a rotor blade is in a position parallel to the polarization of the illumination a 3-blade rotor produces 6 blade flashes per rotation, i. e. when a blade assumes vertical position. The maximum Doppler shift is determined by the blade tip velocity and occurs in a quasi mono-static geometry with the direction of illumination being parallel to the rotation plane of the wind mill rotor. Blade tip velocities of 250 to 300 km/h can be reached.

Wind mill rotors can be modeled as rotating linear scattering objects. Since the rotation is a periodic process, blade flashes are expected to occur whenever a blade is in a position, the time between two flashes, tR is dependent on the number of blades N and the rotation rate fR of the rotor. For a typical 3- blade windmill rotor consecutive blade flashes are caused by alternating approaching and receding blades:

tR=1/(2.N.fR)

Approaching blades yield positive Doppler contributions, while receding blades result in negative Doppler echoes. The spread of the Doppler echo fD(max) is dependent on the bistatic angle β and the blade tip the blade tip velocity component vmax, perpendicular to the bistatic bisector δ.

fD(max)=(2. vmax.cos δ.cos β/2)/λ where v=2.fR.lR.πIn a first approximation the transmitter Tx , the receiver Rx and the centre of the wind mill rotor are considered to be located in the same plane. With lR , the rotor radius being much smaller than the distance between the wind mill and the transmitter or receiver, respectively, the velocity vector can be considered to originate at the centre of the rotor. Figure 2 depicts the geometry.

Figure 2: Bistatic radar geometry for scattering from wind mill rotors

CONCLUSIONS

Stationary targets with a spread Doppler spectrum can clearly be discriminated in the bistatic range/Doppler matrix. By analyzing consecutive snapshots (integration periods) the rotation rate can be determined and from the Doppler spread of single flash snapshots the type of rotor can be deduced. Longer observation times allowing extended echo signal integration can be used to analyze the line structure of the echo spectra.

Track algorithms for passive radar, applied to range/Doppler detections, need to take into consideration the specific scattering properties of stationary, Doppler spread echoes of wind turbines. Identifying wind turbines as such and avoiding tracking them as false targets will reduce the risk that the radar track processors are saturated by ghost targets.

IMPACT MODELLING OF WIND FARMS ON MARINE NAVIGATIONAL RADAR

INTRODUCTION

Offshore wind farms cover large areas of open water and hence present potential hazards to navigation. A number of potential sites are considered to be close to or encroach into waters with a high density of shipping movements or waters used by fishing vessels and recreational craft. Investigation into the

interference by wind farms with ships' radar has confirmed that there may be an impact on radar producing spurious returns on displays caused by multiple reflections, as well as beam spreading and side-lobe detection due to the very high radar cross section of the wind turbine [2].

Unlike air traffic control radars, marine navigational radars are low complexity/cost. The practicality of introducing advanced signal processing into these radars to reduce wind farm impact is considered unlikely [12, 13].

THE WIND TURBINE MODEL

Wind turbines are large structures that are typically made of GRP and/or carbon fibre composite components mounted on steel towers. Pinto [9] shows results of a full physical optics modeling of a wind turbine. This shows the variation in RCS with respect to the rotation angle of the blades and the yaw angle as defined in Figure 3.

Figure 3: RCS modeling coordinate system

The tower constitutes by far the largest source of scatter (approx. 80%) followed by the blades (5% each). The nacelle was only considered to be a significant source of scatter for 90 yaw case (i.e. broadside on). The nosecone was found to be largely insignificant at all angles [8].Current generation of wind farms use turbines with blade lengths of approximately 30 to 40m (60 to 80-m diameter) on a tower of height 70m. As marine navigational radar operates up to X-band, the electromagnetic size of the RCS calculation is already large (many thousands of wavelengths) with the blades of complex shape. While RCS prediction of this size is possible clearly it is non trivial. An additional problem is in a wind farm adjacent turbines are in the near field of their neighbors and may be in the near field of the ship's radar antenna. This significantly increases computational effort.

The turbine was split into sections. The section size ensures that a far field approximation from each section can be used. The RCS values for sections including the nacelle, the blades and the nosecone

across all yaw and rotation angles were taken from a full PO model, so that the shape of the blade is accurately taken into account. Each section is then assumed as a point scattered positioned at the centre the relevant section.

TOWER RCS MODEL

The tower is modeled as a set of cylindrical sections as shown in Figure 2 below. By segmenting the tower into small cylindrical sections, the nearfield RCS can be calculated providing the effective scattering centre for each section is known.

Figure 4: Segmented turbine model

Both mono- and bi-static RCS prediction is required:The monostatic RCS of the tower is used to investigate issues such as the target spreading and side-lobe detection, while the bistatic RCS is required to predict the appearance of ghost targets due to multiple reflection issues.The RCS of each section was obtained using standard simplified physical optics farfield RCS approximations of a cylinder [6] given in Equation (1).

σmono= krh2 [cos(φn)sinc(kh/2sinφn)]2(1)

With information about the radar height and the range, the distance to each segment d is calculated which is used to account for the phase contribution of individual segments.The complex field Vn value at any required for each segment is simply

Vn=[φn/(dn/R)2]1/2 (2)

A complex summation over all segments leads to the required total RCS at a defined point. For the bi-static case the RCS of each section is taken as (see Figure (5)) [10]

σbi=krh2[cos2φ2cos(θ/2)/cosφ1)]sinc2[kh/2(sinφ1+sinφ2)] (3)

Figure 5: Bistatic RCS Layout

Similar to the monostatic RCS, by using Equation (3) to obtain the amplitude of the RCS and the distance d to account for the phase contribution, Equation (2) is then used to find the field Vn value at that point for each segment. This is then added to the rest of the contributions from the other segments to calculate the total bistatic RCS of the tower to a given direction.

MULTIPLE BOUNCE MODEL

When ships are near a wind farm spurious targets appear on the radar display. This phenomenon occurs due to the multiple reflections of radar signals within the farm A ray tracing model has been implemented which calculates successful ray directions from the ship radar to each tower and the direction from anyone tower to any other. The monostatic and bistatic RCS of the tower in the required directions is then obtained from the above model and the field reflected or diffracted to the next tower calculated. The model uses a recursive technique whereby the reflected signal off the tower is traced through as many bounces needed until it reaches a defined threshold value below which it is considered insignificant. The model also allows for potential multiple bounces both from any tower to any other tower and from a nearby ship to the towers. Finally the ray tracing model allows for multiple wanted targets in addition to the wind farm to be introduced.

INTERACTION BETWEEN RADAR SYSTEMS AND WIND FARMS

ABSTRACT

At typical radar frequencies a wind turbine has large radar-cross-section (RCS) and due to the movement of the blades, the wind turbine generates a Doppler spectrum. This scattering behavior has caused concern with radar operators, particularly those working with safety critical radar and national defense.

INTRODUCTION

Due to the threat of climate change, countries around the world are working towards targets for the production of renewable energy. This has encouraged the development of wind farms which are increasing in both the number of turbines in a farm and the size of individual wind turbines.

AEOLUS MODELLING TOOL

A modeling suite has been developed to simulate a radar system in the presence of a wind farm.The code has also been used to provide a prediction of the efficacy of mitigation options by including stealth treatments such as shaping and radar absorbing materials. The code also serves as a useful tool in the analysis of the effect of proposed wind farms and has been used during consultancy for wind farm developers and radar operators.

The tool comprises three integrated modules: Radar Cross Section prediction, propagation analysis and radar system model. Combining all three provides an all-encompassing view of the effect a wind farm has on radar system performance.

PROPAGATION MODELLING

The first step in determining the likely impact of a wind farm on a radar system is to perform line-of-sight calculations. If the radar and wind farm are within line-of-sight then further modeling is conducted to assess the propagation path between the radar and turbines in the wind farm.

The algorithms used include various methods based on Fresnel-Kirchhoff diffraction or the geometrical theory of diffraction (GTD) for single or multiple edges or rough or smooth spherical obstacles, including Giovanelli’s construction for multiple edges [5]. The effects of sub-path attenuation are included when appropriate. Algorithm selection is automatic, based on the terrain analysis, and requires no user input. The effects of atmospheric refraction are incorporated through a variable earth-radius factor which can be adjusted according to the required availability and climatic considerations. If information about the type of ground cover (e.g. vegetation, buildings) is available, it is used to modify the terrain elevation, and to determine a correction factor to account for the immediate environment (“clutter”) around low antennas.

RADAR SYSTEM MODEL

A signal-level simulation model has been developed to investigate the impact of wind farms on radar detection performance. The model synthesizes signals from a wind farm, the environment (clutter), targets and system noise. Clutter and noise are based on appropriate statistical models; the clutter model includes synthesis either sea or land clutter. The radar model consists of typical processing stages, including Moving Target Indicator (MTI), clutter map, Fast Fourier Transform (FFT), Constant False Alarm Rate (CFAR) and thresholding. The model is parametric, allowing the inclusion of processing stage and associated parameters to be defined for a specified radar system. This allows the simulation of a wide variety of radars, such as air traffic control, meteorological and air defence. The model includes a Graphical User Interface (GUI) for easy data input.

The model synthesizes returns for radar pointing in a given azimuth and elevation direction. Various radar parameters may be specified, including peak transmit power, Radio Frequency (RF), receiver bandwidth (for noise calculations), range resolution, range side lobe level, Pulse Repetition Frequency (PRF) and losses.

Several radar scans may be emulated. On each scan the complex-valued I and Q signal for clutter, target, noise and the specified wind farm are calculated and summed coherently. Clutter, noise, target and wind farm parameters are specified through the GUI, as shown. Clutter may be land or sea clutter. K-distributed clutter with appropriate Gaussian-shaped spectral density is calculated over the coverage in the radar main-beam. Wind farm parameters include positions and RCS values stored in files, and also blade aspect angle, rotation angle, site and tower height and rotation speed.

Radar processing is performed emulating the typical algorithms performed in radars, including MTI and FFT. Several types of thresholding options are available, including clutter map and CFAR. Threshold output is presented in an appropriate manner. Other intermediate outputs are displayed, including clutter map thresholds and power levels of processed signals.

A number of observations can be made.

i) The wind farm returns are stronger in the face-on case since blade RCS is larger. The MTI has not completely attenuated these returns because, due to blade tilt back (of 5°) blade Doppler is non-zero.ii) In both cases there is a spread of turbine returns in range. This is due to the pulse compression waveform used by the radar.iii) In both cases there is a spread of turbine returns in azimuth angle due to leakage of main turbine returns in the side lobes of adjacent beams.iv) The speckled returns observed out to approximately 56km represent the ground clutter returns not filtered by the 3-pulse MTI.

CONCLUSIONS

The model includes specified turbine type, wind farm layout, radar location and local terrain and radar system processing stages and operating parameters. To illustrate the use of the model and demonstrate the typical effects a radar system has on a wind farm, a case study was considered.

The case study has shown that a wind farm may cause small aircraft to be undetected if they fly over or in the vicinity of the farm. The use of pulse compression by radar causes leakage of turbine returns in adjacent range gates due to range side lobes and thus elevated thresholds. In addition, where range-acting CFAR thresholds are used to maintain constant false-alarm, contamination of the CFAR averaging window by turbine returns also causes elevated thresholds in the vicinity of the farm. Furthermore, where azimuthally beam scanning is employed, beams pointing adjacent to a wind farm may be contaminated by sidelobe leakage of turbine returns.

Investigation of Doppler Features from Wind Turbine Scattering

INTRODUCTION

THE rapid growth in the number of wind farms has raised serious concerns in the radar community about their effects on existing radar systems [1], [2]. The large size and rotational movement of the turbine blades can give rise to significant Doppler clutter, which interferes with the detection of moving targets such as aircraft and storms.

The most significant feature in the backscattering RCS and the Doppler processed data was found to be the blade flashes that occur when the blades are oriented perpendicular to the radar line of sight. At all other positions of the blades, the blade tip was observed to trace a sinusoid in the spectrogram as it rotated. These results are quite similar to helicopter rotor blades, whose Doppler characteristics have been well studied previously [5]–[7].

In addition to these prominent features, other Doppler tracks were also observed in the data. They are potentially caused by higher order multiple interactions, but were not fully explained. Furthermore, only the backscattered data of a single turbine was taken. The transmission blockage effect due to the wind turbine was not characterized in the study, which would have required a one-way forward-scattering measurement with the transmitter and receiver being positioned on the two sides of the turbine.

In this letter, we set out to more closely examine the Doppler features in wind turbines through a series of scaled model measurements. Both backscattered and forward-scattered data are measured at Ku-band from various wind turbine models undergoing rotation. The tested models include a 1:160 scale model turbine, a three-arm wire model, and a small wind turbine from Bergey Windpower with 20 blades.

We present detailed accounts of the physics behind the observed phenomena including multiple scattering, near-field effects, and blade shape effects. We first report on the results of the 1:160 scaled model turbine and show that our scaled model measurements capture the gross Doppler features observed in [3], [4].We then describe the multiple scattering and near-field effects observed in the wire model turbine.

The experimental findings are corroborated by simulations performed using the Numerical Electromagnetics Code (NEC). For forward scattering, it is shown that Doppler features can only arise due to multiple scattering.

METHODOLOGY

Clearly seen are the blade flashes that occur at every 60 turn of the turbine. The flashes alternate between positive Doppler (as a blade moves toward the radar) and negative Doppler (when the next blade recedes away from the radar). In addition, a set of weaker, sinusoidal Doppler tracks can be observed. They are due to scattering from the blade tips and are labeled as “tip halo” in the figure. As the yaw angle is changed from 900 to 00 (nose-on), the amount of Doppler shift decreases as the radial velocity of the blades with respect to the radar is decreased.

Several new features are noted in addition to the blade flashes and tip halos discussed previously. First, we see from the backscattered spectrogram an additional sinusoid track that is in phase with the tip halo [labeled as (i)]. This additional track is due to a traveling wave along the wire from the tip to the hub, and vice versa, as illustrated in Fig. 3(a). The blade in Fig. 3(a) rotates clockwise, and the bottom end of the blade is the center of rotation. Therefore, the two traveling waves along the wire in Fig. 3(a) experience a path length change versus time that is only half as large as the direct scattering due to the top tip. Hence, this interaction results in a Doppler track with a maximum Doppler shift equaling half that of the tip halo.

Figure 6: (a) Backscattering mechanism (i). (b) Forward scattering mechanisms (ii) & (iii).

For the forward scattering case, in the interaction labeled as (ii), the wave experiences a decrease in path length as a function of time since the top tip moves toward the transmitter. However, in traveling down to the base of the wire and toward the receiver, no additional path length change is encountered. Therefore, this interaction gives rise to a sinusoid that has a positive Doppler shift with maximum equal to half that from the tip halo backscattering.

The case labeled as (iii) in Fig. 6(b) gives rise to a negative sinusoidal peak since the wave experiences an increase in path length as a function of time as it travels from the top tip to the receiver. We note that while the Doppler features in backscattering arise from both single and multiple scattering, forward Doppler can only result from multiple scattering interactions. Any single scattering phenomenon will result in only zero Doppler contribution in the forward direction.

Lastly, we observe that the blade flashes in the backscattering. Fig. 7(a) also explains why this track peaks on the opposite side of the blade flash. The two blades involved in the interaction are at 300 to the horizontal, hence the maximum Doppler value of v/λ. interblade interactions that result in a maximum Doppler shift of √3v/λ along with the tip-to-base interaction described earlier, which gave rise to a maximum Doppler of only v/λ.

Figure 7: (a) Backscattering mechanisms (i) and (ii). (b) Forward scattering mechanisms (iii) & (iv).

In fig.7 (b) we notice that while tip-to-base interaction tracks peak when the blade is perpendicular to the incident wave, tip–base–tip interaction peaks when the blades are 60 to the horizontal. Because of the three-bladed symmetry of the structure, the tracks for the backscattered data change signs every 600, while forward-scattered Doppler tracks are repeated after every 600 rotation.

To understand the irregular flashing behavior in the backscattering, we consider a simpler model comprising triangular-shaped turbine blades shown in Fig. 7. In Fig. 7, the blades are assumed to rotate clockwise. For this simple model, the edge of the triangular turbine blade does not become perpendicular to the radar in the orientation shown in Fig. 7(a), but at θ 0 later (where 2θ0 is the inscribed angle of the blade). This results in a delayed flash, as marked by the first black line in Fig. 7(c). The next flash also does not occur in the position shown in Fig. 7(b), but at θ0 earlier. Therefore, the interval between two flashes is decreased by 2θ. On the other hand, the next interval is lengthened by 2θ.

Figure 8: Blade shape effect based on a simple triangular blade model (a) θ0 before a blade flash occurs (b) After 600 of rotation (c) Resulting irregular blade flashes as shown in black.

Fig. 8(c) illustrates this effect. The light flashes shown are normal equally spaced flashes that are 600 apart. The black flashes shown are from a triangular-shaped blade occurring in the angular intervals described above. Note that even for a small θ value of 150, the adjacent flash spacing becomes 300 –900 instead of 600 –600.

Conclusion:For the three-arm wire model, additional multiple scattering and near-field effects were observed and interpreted with the aid of simulations performed using NEC. It was also found that only multiple scattering gives rise to nonzero forward Doppler. For the Bergey Windpower turbine, we observed unequally spaced, curved flashes. They are attributable to the unique shape of the turbine blade.

Methodology for the Empirical Analysis of the Scattering Signals from a Wind Turbine

Abstract

The method is based on the scattering pattern of the wind turbine, empirically obtained from the estimation of the Channel Impulse Response, which allows the accurate estimation of the amplitude and the time variation of the scattered signals. The analysis of the Channel Impulse Response at different situations, such as the rotation speed, the orientation of the turbine or the elevation and azimuth angles of the receiver location, will allow the proper characterization of this phenomenon, and therefore, the development of an empirical model for the estimation of the potential interference of wind farms.

INTRODUCTION

The wind farms, located in some cases close to the existing transmitter sites, can degrade the quality of existing communications systems, especially in radar services[1],[2].The potential impact of wind turbines in the radar services can have three different consequences: first, the wind turbines may block the radar beam, and therefore, this may cause erroneous hydro-meteorological measurements in significant geographical areas behind the wind turbines; secondly, high clutter levels that blind the radar receiver in the area where the wind farm is located; and last, the rotating blades generate interfering signals in the Doppler reception mode [1], [8]-[10].

OBJECTIVES

This paper proposes a field data-based methodology to characterize the scattered signals from wind turbines, in order to evaluate the potential interference of wind farms. The methodology will provide a model based on the scattering pattern of the wind turbine, empirically obtained from the estimation of the Channel Impulse Response.The scattering pattern considers parameters related to the dimensions and materials of the wind turbine, the static and the moving parts of the elements of the wind turbines, and the scattering and obstruction effects between these elements in different situations. The variation of the scattering pattern with azimuth and elevation angles is also included in the methodology. The Channel Impulse Response will allow the accurate estimation of the amplitude and the time variation of the scattered signals.

ANALYSIS AND METHODOLOGY

The first step is the planning and development of field trials that provide empirical data for different situations. The assessment of the Channel Impulse Response at each measurement point will allow the characterization of the scattered signals from each wind turbine in different situations along the time.

The definition of other aspects such as the Doppler effect of the rotating blades or the amplitude modulation of the scattered signal should be considered in this point. Then, the most influential parameters that characterize the phenomenon must be selected, and the variability of each parameter determined. Last, the model that will allow the estimation of the impact of a specific wind turbine must be defined.

A. The Use of the Channel Impulse ResponseIn the vicinity of the wind farm, the electromagnetic waves scattered by the wind turbines are received as echoes of lower amplitude with respect to the direct ray from the transmitter. The Channel Impulse Response will contain this information, and therefore, it is a useful tool for the identification of the scattered signal on each turbine, and for determining the amplitude of all of them. As illustrated in the Fig. 1, the Channel Impulse Response will contain, apart from the direct ray, delayed signals that arrive at

the receiver location with lower amplitude. These components correspond to the reflected signals on the wind turbines.

Figure 9: Channel Impulse response

The delay of the echoes can be theoretically calculated for a specific reception point, from the difference between the propagation time of the reflected ray (transmitter – wind turbine - receiver) and the propagation time of the direct ray (transmitter - receiver). The assessment of the theoretical delays allows the association of each echo to a specific wind turbine, as it is depicted in the Fig. 1. As a result, accurate values of the power of the reflected signals can be obtained from the Channel Impulse Responses for every wind turbine.

B. The field trials

The obtaining of detailed Channel Impulse Responses (with a resolution of at least tenth of microseconds) requires the recording of a signal bandwidth of several MHz. Moreover, the analysis of the variation with time of the scattered signals, as the blades rotate, requires the real-time signal recording during several seconds. All these severe requirements lead to the use of advanced RF signal recorders, with very high sample rate of a span of several MHz and a high bit resolution [19].

C. Description of the phenomenon

The parameters of the wind turbine that must be considered are:

The dimensions and materials of all the elements that form the wind turbine: the metallic mast, the nonmetallic blades and the metallic nacelle.

The differentiation of the effect of the static and moving parts of the turbine: the mast is static, but the blades and the nacelle are moving parts. The nacelle moves bearing against the wind, and the blades vary the pitch angle, the rotation speed and the orientation along the time [2].

The influence of the three types of movements related to the blades (pitch, yaw and rotation) must be considered in the analysis. The pitch angle is related to the section of the blade that faces the electromagnetic wave, the yaw angle is related to the section of the blade and to the Doppler effect, and the rotation speed is related to the Doppler effect and to the variability of the scattered signals, mainly.

The rotating blades may cause periodical obstruction of the incident electromagnetic wave on the metallic mast. Consequently, the amplitude of the scattered signal from the mast may vary periodically.

Other aspects, such as polarization, signal modulation and variation with frequency should be considered.

Taking into account the previous considerations, at least four different situations should be included in the empirical analysis:

Wind turbines under normal operation (rotating blades). Wind turbines with static blades. Wind turbines with static blades controlling the rotor orientation. That is, the rotor is forced to

turn around, controlled by the yaw engines, with constant pitch. Wind turbines with static blades varying the pitch of the blades (the angle of the blades can be

actively adjusted by the pitch control system in order to control the power output), with constant rotor orientation.

The last two types of measurements are very useful for the characterization of the scattered signals, because allow the evaluation of the scattered signal variation for a specific factor (pitch variation or rotor orientation).

D. Determining the most influential parameters

The scattering pattern variation in both the horizontal plane (azimuth angles) and vertical plane (elevation angles) must be also included in this point. The elevation angle accounts for the difference in height of the transmitter, the wind turbine and the receiver location. The variation with the azimuth angle will determine the directions where the scattering signals have higher amplitude. Accordingly, measurement points for evaluating different elevation and azimuth angles from the wind turbine must be considered in the field trials.

E. Definition of the model

Once the proposed methodology has been applied, the empirical model should be based on the most influential aspects included in the study:

The dimensions and materials of the elements that form the wind turbine. The effect of the static and moving parts of the turbine. The different movements of the blades (pitch, yaw and rotation). The existence of reflection and/or obstruction of each element of the turbine in different working

regimes. The scattering pattern variation in both the horizontal plane (azimuth angles) and vertical plane

(elevation angles).

Numerical Simulations of Environmental Distortions by Scattering of Objects for the Radar RCS and Wind turbines

INTRODUCTION

The radar systems work according to its intended performance in the absence of distortions. These distortions are often caused by objects which are located relatively close to the radar. These objects may be existing buildings in case of relocated radar or newly built or planned objects such as wind turbines in some distance to the ATC, military or weather radar. The operator wants to know in which way these objects will harm the performance of the radar. The radar must meet its intended tasks under the impact of the objects. On the other hand "no distortions" or "no risk" is technically also unfeasible. Often it is not unique and not obvious if the "effect" is a distortion or a matter of discomfort and not a real threat for the radar.

OBJECTS ON THE GROUND AND RADAR; RCS

An actual widely discussed example of a distorting object is the case of wind turbines WT and radar, in particular the weather radar WR. The typical WR [7] has a pencil beam of 10 beam width. The WR is sampling the space by periodic scanning. The lowest elevation beam position is 00 to about 0.70 at the horizon. By that the ground effects for these low elevations create the lobing of the elevation pattern as a normal feature for a WR. The WT are illuminated too in these positions and superpose a bit in small volumes only.

For a modern typical WT, the nacelle may be in a height of 80m. This results in an elevation angle of about 0.60 assuming a distance of the WT of 5000m and a local height of 30m. It is common to characterize the objects for the radar by the RCS (σ, radar cross section; mono-static, bi-static).

The general definition of the RCS (1) [4] assumes an asymptotic infinite distance. That implies the plane wave excitation or a real far-field approximation [4], [5], [6], [8] .The plane wave is characterized by constant amplitude and by a linearly progressing phase across the object. The WT are naturally installed on the ground and by that the ground interactions have to be taken into account for the lowest beam positions which are relevant for the WT only.

The mono-static RCS of a WT in free space is extremely structured and lobed due to the electrically large size of the WT. The RCS is also very sensitive for the spatial direction. By that again, strictly speaking the RCS is different for the direct signal and the ground reflected signal also. Large amplitudes in narrow peaks ("flashes") and interference are superposing an average RCS generated by the conical frequently metallic shaft. The RCS of lattice type shafts is typically much lower.

The effects of the ground are twofold, for the excitation caused by the radar at the WT and for the echo response scattered by the WT at the location of the WR. The WR has some height above ground and the WT effectively .By that, two sources of fundamental errors occur if the RCS-scheme is applied to the WR/WT case, namely the non-existence of the plane waves for the validity of the RCS and the distorted lobing field amplitude in the scattered response at the location of the WR.

A further interesting technical issue of the WT with regard to the pulse-Doppler-WR and the RCS is that of the rotating blades. The blades may rotate up to 22/min. By that their radial velocity may be up to 300km/h at the tips and a high Doppler-shifted frequency may be created by the rotation (up to about 3 kHz for the C-band WR). Typical WR measure a maximum wind/cloud speed uniquely up to about 1l km/h having a typical real resolution of about 1 m/sec. The amplitude of the Doppler shifted signals depends on many factors such as the orientation of the WT and the back scattering properties of the blades. However, in any case the Doppler shifted back-scattered signal represents a continuous spectrum and contains positive and negative Doppler shifts. By that again, the simple stationary monostatic RCS of the blades is not representative for the rotating blades. In fact, the RCS is distributed and much reduced by the Doppler spectrum.

One can define a RCS-frequency-function in dBsm/Hz. One can understand that easily since only a small subpart of the blades creates the related Doppler frequency and not the total blade. Only in case of the non-rotating stationary blades the total blades contribute to the Hz-signals which are suppressed by the MTI/MTD mechanism by 40dB minimum in case of modern radar.

CONCLUSION

Two radar problem areas have been discussed theoretically and by numerical results. The simple stationary theory of radar cross section RCS is strictly speaking not applicable for objects on the ground such as wind turbines with regard to radar in general and also not for the weather radar. The RCS of the total stationary blades is not applicable for the Doppler-evaluation.

The error made by a worst-worst-case analysis (RCS, Doppler) is unpredictable and can be very large. By that, the RCS does not seem to be adequate for the definition of safeguarding distances for wind turbines related to radar. A deterministic state-of-the-art scattering analysis has to be carried out which takes into account the 3D-model of the wind turbines and the relevant electrical features and the geometry of the radar in relation to the wind turbine.

On the Relevance of the Measured or Calculated RCS forObjects on the Ground - Case Wind Turbines

INTRODUCTION: WIND TURBINES AND RADAR

Wind turbines are installed in a rapidly increasing number often due to different constraints in some distance to radar systems, such as Air Traffic Control, Defense Radar and Weather radar. The WT do have “effects” on the radar performance which have to be determined in some way in the course of the application and approval process of the WT and wind parks. By that, there is a principal and classical conflict between the assigned specified task and mission of the radar and the installation of the turbines for the sake of renewable energy which has an increasing priority in the countries and societies worldwide.

The easiest ways if possible seem to be to install the turbines (“sufficiently”) far away and/or to modify the wind turbines for minimized tolerable effects. To determine this crucial distance the RCS (Radar Cross Section) is often tried to be used by radar operators who are used to dealing with the RCS and who tend to stick to the RCS.

It has been shown in several papers by the author ([7] - [10], [12], [13]) that the RCS is not applicable for objects on the ground due to fundamental theoretical reasons which seem to contradict the “radar experience”. This paper shall add on one hand more arguments and results to support this position of the general non-applicability of the RCS for wind turbines in particular and for objects on the ground in general. On the other hand, numerical results are shown for the RCS under different scenarios using the correct definition. These results are also related to the question of the applicability of the RCS for the safeguarding.

The term “relevance” in the title has intentionally an ambivalent meaning, indicating that the result of this paper is that the RCS of WT is irrelevant for the safeguarding of radar.

INTRODUCTION RCS; DEFINITION AND CONSEQUENCES

A. RCS Theory

The Radar Cross Section RCS is a widely used classical scheme to characterize a target for radar for the determination of the maximum range and visibility. The RCS (σ, radar cross section; mono-static, bi-static) is defined explicitly for a plane wave excitation [2].

It is a useful parameter for objects of limited size in space such as the aircraft or other flying objects (high) above ground. The remark “high above ground” means simply that the ground is not illuminated by the radar in a relevant way. The general definition of the RCS (1) [2] assumes an asymptotic infinite distance. That implies the plane wave excitation or a real far-field approximation [1], [3] - [6]. By that, the RCS is a far field quantity such as the gain of an antenna.

σ contains the obligatory limit condition R→ ∞ which implies a plane wave excitation as explained also in the IEEE definition of terms explicitly [2]. The plane wave is characterized by constant amplitude and by a linearly progressing phase across the object. A single harmonic frequency is also assumed implicitly and, by that, Doppler shifted back-scattering spectrum ([7] – [10]) is not covered by the original RCS-scheme.The monostatic RCS is a normalized power quantity, i.e. normalization of the scattered power (= squared scattered total field strength) to the incident power at the location of the total object.This RCS figure is used widely in radar for the determination of the maximum range Rmax by the well known formulas.

Because the RCS depends on the total scattered electric field of the total object, it has to be expected that in general the RCS of electrically very large and asymmetrically structured objects is very much structured in small angular scales. By that the numerical calculation or the measurement of the RCS must be processed with the adequate resolution.

Because the RCS depends on the total squared scattered electric field of the total object, RCS quantities cannot be added. In the given case of the WT the total RCS of a WT is not the sum of the RCS of the sub-parts. Also the RCS of a wind park is not the sum of the individual RCS.

B. RCS and Scattering of a Wind Turbine; Dependencies

The RCS and the scattering of a WT depend on many factors in a characteristic way1. Frequency and polarization of operation2. Geometrical / electrical size3. Form and geometrical structure, e.g. type of mast, form4. Materials used (e.g. mast: concrete, metallic, lattice)5. Direction of the wind (aspect angle of the nacelle and the blades)6. Position of the rotor blades in case of no rotation7. Form, material and construction of the rotor blades (e.g. glass fibre, carbon fibre, lightning

arrestor)8. Rotation of the blades (case 1: very slow rotation with negligible Doppler shift)9. Rotation of the blades (case 2: noticeable or relevant Doppler shift of parts of the re-scattered

signal; max about 22rpm)

Due to the large number of factors it is clear from the very beginning that a unique number for the RCS cannot exist at all as often requested.The realistic and really important (back) scattering depends on several more parameters

1. Radiation characteristics of the radar (antenna pattern; e.g. pencil beam, shaped cosec beam)2. Distance between the radar and the WT3. Height of the radar above ground taking into account the ground effects. The electrical height is

usually very large and a fast elevation lobing has to be expected [9].4. Relative height of the radar and the WT.5. Height of the WT above the average ground taking into account the ground effects on the back-

scattering

Due to the large number of additional factors it is clear from the very beginning as well that the (back) scattering of a WT is very much site and case dependant.

C. “Nearfield RCS”

The RCS is per definition a farfield quantitiy. The farfield distance is by the large structure also very large.By that the term “nearfield RCS” is misleading and seems to suggest that a different RCS would exist in the nearfield.Also, a different scheme to determine the farfield RCS on the basis of some nearfield measurements and transformation to the farfield RCS does not justify a new term. The measured or calculated nearfield quantities must be based anyhow on the excitation by planes waves or approximated spherical waves originating in some shorter distances, transformations by algorithms and in case some calibration. In any case the socalled “nearfield RCS” is an approximation of the real farfield RCS and not a new quantity.

D. Reduced RCS; “Stealth” WT

The effects on radar by the WT are caused by reflections and/or scattering at the WT which includes the “forward scattering” causing the “shadowing”. In order to reduce the reflections several methods are

proposed: absorbing material in the blades and/or generally designing the WT in a way to have “stealth capabilities” for the monostatic backscattering by forming the surface in addition. This target should have broad band characteristics and should work under all operational conditions such as rain and ice conditions. Strong rain will destroy most likely all mitigation measures based on absorbing material due to the high dielectric constant of water.

Also it should not worsen the situation for one radar system (e.g. secondary radar affected by bistatic scattering) while improving it for another radar (e.g. primary radar). Locations are known where the WT are in the radiation field of 2 separated radar. It should be reminded too that the forward scattering (i.e. the shadowing) cannot be affected by most stealth principles.

A calibration of the measured RCS above ground by a sphere above ground as proposed [14] suffers from the problem of the ground effects as well and the results seem to be highly problematic [11] and arbitrary generally.

RCS consists of the basic omnidirectional basic figure of the symmetric shaft and oscillating components by the nacelle and the metallic blades. The RCS is independent of the radar characteristics (pattern, power) and independent of the distance of the radar. However, real effective back-scatter does depend very much on the distance, i.e. for operationally the most important distances in the considered range between 5km and 15km.

The RCS is very variable due to environmental parameters such as the wind direction and wind speed. This is in particular for the scattering from the blades and the Doppler spectrum. The backscattered signal has in case of rotating blades a Doppler spectrum because the radial speed of the turning blades is different along the blades. The strict RCS-theory assumes a mono-frequent case, i.e. the stationary blades. The back scattered signal consists of a non-frequency shifted component and Doppler-shifted components, i.e. the spectrum.

The ratio of the amplitude of the zero spectrum component to the amplitude of the Doppler shifted spectral line depends on the width of the considered frequency band spread. The spectrum is typically measured or simulated by a sliding bandfilter. This applies for the numerical simulations as well as for the measurements. By that measured or simulated results are not unique and have to be interpreted for their application for particular radar. The decisive point is the signal processing in the considered radar. Each radar is different in principle (MTI/MTD filtering).

Conclusion

Idealized RCS which is defined and determined in free space without the ground is not a useful valid figure to evaluate the distortion effects of real installed WT on the ground. This correctly calculated or measured RCS according to the standard definition does not describe the physical reality if the ground is illuminated significantly. If the ground is not illuminated by a pencil beam pointing to higher angles, then it is very obvious that the WT is illuminated only partially and that the back scatter is different from the RCS-scheme as well. The errors are unpredictable.It has been discussed that a “nearfield RCS” does not exist in a sense that it would be a new figure on top of the standard RCS. The dynamic of the RCS is very large and the application of the large RCS tends to exaggerate the effects much and, by that, to exaggerate the safeguarding distances.

It has been discussed that mitigation measures to suppress the RCS by absorbing material or shaping to stealth principles cannot meet the requirements of general applicability for all environmental conditions or all radar types, e.g. primary and secondary radar or if the WT is illuminated by two radars at different locations.