EIWAC2017 (Nov. 16th 2017)

○ Daichi TorataniHiroko Hirabayashi

Air Traffic Management DepartmentElectronic Navigation Research Institute

Akiko KohmuraSurveillance and Communication Department

Electronic Navigation Research Institute

Simulation Techniques for SmallUnmanned Aircraft Systems (sUAS)

Trajectories including Signal Propagation

Table of contentsEIWAC 2017

Nov. 16th 2017

Daichi Toratani

01/16

1. Introduction

- Future sUAS operating environment

- Simulation techniques for sUAS safe operation

2. Research outline

- Radio communication for sUAS

- ADS-B for sUAS

3. Simulation methods- sUAS trajectory simulation

- Radio signal propagation simulation

4. Simulation results- Simulation conditions

- Estimated ADS-B signals at receiving station

5. Conclusion

1. IntroductionEIWAC 2017

Nov. 16th 2017

Daichi Toratani

Future sUAS operating environment

The demand for small unmanned

aircraft system (sUAS) increases.

• Infrastructure inspection

• Logistics

• Pesticide application

• Land Survey

UAS Traffic Management: UTM (NASA)Safety problems

Low-level airspace (class G)

Near miss!

* No ATC service

1. IntroductionEIWAC 2017

Nov. 16th 2017

Daichi Toratani

C. Russell et al. (2016)K. Krishnakumar et al. (2017)

• Computed Fluid Dynamics (CFD)

in urban environment

• Wind tunnel test

Simulation techniques for sUAS safe operation

Simulation of future sUAS

operating environment

Lift

Drag

Momentum

⋮

Radio wave environment for sUAS

Wind

Collision

avoidance

VFR

aircraft Human

factor

BVLOSFPVRisk

analysis

03/16

Table of contentsEIWAC 2017

Nov. 16th 2017

Daichi Toratani

1. Introduction

- Future sUAS operating environment

- Simulation techniques for sUAS safe operation

2. Research outline

- Radio communication for sUAS

- ADS-B for sUAS

3. Simulation methods- sUAS trajectory simulation

- Radio signal propagation simulation

4. Simulation results- Simulation conditions

- Estimated ADS-B signals at receiving station

5. Conclusion

04/16

• Communication

• Command

• Control

C3link

2. Research outline

Radio communication for sUAS

Command

ControlMovie

Flight data

Communication

Interference!

Risk of clash

Simulation and assessment

Increasing sUAS

Increasing radio emission

Radio waves will interfere.

Interference affects

radio communication.

Simulation techniques for radio

environmental simulation.

EIWAC 2017

Nov. 16th 2017

Daichi Toratani

05/16

The Interference depends on:

• Radio power

• Traffic density

R. M. Guterres et al. (2017)

Radio environment and sUAS movement

2. Research outline

2.4GHz 1090MHz

Radio communication equipment

LTE 5GHzWi-Fi

sUAS movement Multi-copter

Fixed-wing

Helicopter - Anywhere

- Anytime

Simulating individual radio signal and sUAS trajectory in parallel

EIWAC 2017

Nov. 16th 2017

Daichi Toratani

06/16

Automatic Dependent Surveillance - Broadcast

(ADS-B) for sUASAir-to-ground Air-to-air

MonitoringDetect and avoid

(DAA)

2. Research outline

Receiving

station

Own sUAS

Operator

Command

Control

Other sUAS

ADS-B out

ADS-B out ADS-B in

• sUAS are equipped with ADS-B out.

• The operator can obtain information

via receiving station.

• The receiving station can not decode

the signal with interference.

• A coupling simulation between

trajectory and radio signal is

performed.

EIWAC 2017

Nov. 16th 2017

Daichi Toratani

07/16

Table of contentsEIWAC 2017

Nov. 16th 2017

Daichi Toratani

1. Introduction

- Future sUAS operating environment

- Simulation techniques for sUAS safe operation

2. Research outline

- Radio communication for sUAS

- ADS-B for sUAS

3. Simulation methods- sUAS trajectory simulation

- Radio signal propagation simulation

4. Simulation results- Simulation conditions

- Estimated ADS-B signals at receiving station

5. Conclusion

08/16

3. Simulation methods

• Three-degree-of-freedom model

𝑑2

𝑑𝑡2

𝑥𝑦𝑧

=

Τ𝑓𝑥 + 𝐷𝑥 𝑚

Τ𝑓𝑦 + 𝐷𝑦 𝑚

−𝑔 + Τ𝑓𝑧 + 𝐷𝑧 𝑚

• Integral calculation with 4th order

Runge-Kutta method

WP𝑖

WP𝑖+1𝑉ℎ,𝑖+1

Deviation

𝑥

𝑦𝑧

𝑓𝑥 + 𝐷𝑥

𝑓𝑦 + 𝐷𝑦𝑓𝑧 + 𝐷𝑧

Mission plan Horizontal control

sUAS trajectory simulation

EIWAC 2017

Nov. 16th 2017

Daichi Toratani

Quadrotor-type

𝑚𝑔

Velocity control

+

Path following

Position VelocityHolding

time

Take off 𝑥𝑡𝑘𝑜, 𝑦𝑡𝑘𝑜 , 𝑧𝑡𝑘𝑜 0, 𝑉𝑧,𝑡𝑘𝑜 𝑡𝑡𝑘𝑜

WP1𝑥1, 𝑦1, 𝑧1 𝑉ℎ,1, 𝑉𝑧,1 𝑡1

WP2𝑥2, 𝑦2, 𝑧2 𝑉ℎ,2, 𝑉𝑧,2 𝑡2

⋮ ⋮ ⋮ ⋮

WPf𝑥𝑓 , 𝑦𝑓 , 𝑧𝑓 𝑉ℎ,𝑓 , 𝑉𝑧,𝑓 𝑡𝑓

Land 𝑥𝑓 , 𝑦𝑓 , 𝑧𝑙𝑛𝑑 0, 𝑉𝑧,𝑙𝑛𝑑 -

09/16

Simulation conditions

• Grid: 300 m square

• Altitude: 120 m

• Velocity: 2 m/s (horizontal)

1 m/s (vertical)

Simulation example (trajectory)

x : Waypoint

• The sUAS can fly as following

series of the waypoints.

• The sUAS can maintain both

horizontal and vertical target

speeds.

3. Simulation methodsEIWAC 2017

Nov. 16th 2017

Daichi Toratani

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3. Simulation methods

𝑙𝑜𝑠𝑠(𝑡) =)4𝜋𝑅(𝑡

𝜆

2

Radio signal attenuation:

Free-space propagation model

Assumption

• There are few radio obstacles.

• Fading and Doppler effects are not considered.

Radio signal propagation simulation

Oscilloscope

ping1090

0.5 s

Directory-measured ADS-B signal.

EIWAC 2017

Nov. 16th 2017

Daichi Toratani

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112 𝜇s

Frequency: 1090 MHz

Power: 20 W

Table of contentsEIWAC 2017

Nov. 16th 2017

Daichi Toratani

1. Introduction

- Future sUAS operating environment

- Simulation techniques for sUAS safe operation

2. Research outline

- Radio communication for sUAS

- ADS-B for sUAS

3. Simulation methods- sUAS trajectory simulation

- Radio signal propagation simulation

4. Simulation results- Simulation conditions

- Estimated ADS-B signals at receiving station

5. Conclusion

12/16

4. Simulation results

Assumptions

• All the sUAS start to emit

radio from takeoff.

• No wind

• No other radio wave

Simulation conditions

EIWAC 2017

Nov. 16th 2017

Daichi Toratani

sUAS1

Initial position Takeoff time

sUAS1 (0, 0) 10

sUAS2 (-5000, 5000) 10

sUAS3 (2000, 2000) 10

sUAS4 (-8000, 8000) 10

sUAS5 (5000, -5000) 20.2

sUAS2

sUAS3

sUAS4

sUAS5

Receiving station

(x, y, z) = (0, 0, 2)

13/16

sUAS1

sUAS2 sUAS3

sUAS4 sUAS5

4. Simulation resultsEIWAC 2017

Nov. 16th 2017

Daichi Toratani

Trajectories

14/16

sUAS1

sUAS2

sUAS3

sUAS4

sUAS5

Receiving station

(x, y, z) = (0, 0, 2)

4. Simulation results

• The difference in the sUAS trajectory

affects the radio wave.

• Distance between a sUAS and the

receiving station affects the signal

level and phase.

• The signal phase also varies because

of the takeoff time.

Estimated ADS-B signals at the receiving station

EIWAC 2017

Nov. 16th 2017

Daichi Toratani

15/16

sUAS1

sUAS2

sUAS3

sUAS4

sUAS5

Receiving

station

sUAS1

sUAS2

sUAS3

sUAS4

sUAS5

Receiving

station

5. Conclusion and future works

• This study presented a technique for sUAS trajectory

simulation that includes radio signal propagation of

the ADS-B.

• The ADS-B signal mainly depends on the distance

between the sUAS and receiving station.

• The takeoff time also affected the ADS-B signal.

• Future work will include:

- a hardware-in-the-loop test to investigate signal

decodability of the ADS-B.

- the attitude angle of sUAS to review

the effects of directivity of the antenna.

EIWAC 2017

Nov. 16th 2017

Daichi Toratani

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