Radar System Design with Phased Array System Toolbox John Zhao Product Manager

Transcription

1 Radar System Design with Phased Array System Toolbox John Zhao Product Manager 2013 The MathWorks, Inc. 1

2 Outline Challenges in Radar System Design Modeling Pulse Radar System Modeling FMCW Radar System Designing Phased Array Integrating and Prototyping Radar System 2

3 What is Radar? Waveform Generator TX Transmitter Transmitted signal Environment, Targets, and Interference Signal Processing RX Receiver Echo signal Delay = position Doppler shift = speed 3

4 Radar Design Requires Multi-Domain Expertise and Collaboration Signal modeling in 3 domains: Time domain Frequency domain Spatial domain System development in 3 domains: Digital Baseband Analog/Mixed-Signal Radio Frequency Waveform Generator Signal Processing Transmitter Receiver Environment, Targets, and Interference 4

5 Phased Array System Toolbox Design and simulate phased array radar systems Arrays, waveforms, targets, clutter, etc Normalized Doppler Frequency Power (db) Normalized Doppler Frequency Power (db) Radar signal processing algorithms 0.5 Data Snapshot Angle Doppler Response NonfluctuatingCoherent Receiver Operating Characteristic (ROC) Curves Angle (degrees) SMI Weights Angle Doppler Response P d SNR=13dB SNR=10dB SNR=3dB SNR=0dB Angle (degrees) P fa 5

6 Outline Challenges in Radar System Design Modeling Pulse Radar System Modeling FMCW Radar System Designing Phased Array Integrating and Prototyping Radar System 6

7 Pulse Radars Applications Established technology Defense: Outer space / marine surveillance Antimissile / guided missile target locating Civil: Altimetry and flight control Air traffic control and aircraft anti-collision and more: Weather monitoring Ground-penetrating radar for geological observations Radar astronomy 7

8 Example: Pulse Ground Radar Measure distance, speed and direction DSP 8

9 What Behavior Can Be Modeled? Waveform design Channel model (interference, clutter) Target model Algorithms for Data Analysis Antenna arrays (size, geometry) RF impairments (noise, non-linearity, frequency dependency) 9

10 Which MathWorks Tools Can Help? Phased Array System Toolbox Waveform design Array design Radar equation Channel model Target model Detection algorithms SimRF Component noise Component Non-linearity Carrier frequency selectivity 10

11 System-Level Block Diagram Waveform Generator Transmitter Environment, Targets, and Interference Signal Processing Receiver 11

12 Power (db) Amplitude (v) Waveform Generation Pulsed waveforms Rectangular pulses Linear frequency modulation (LFM) pulses Stepped FM pulses Staggered PRFs Phased coded waveform Continuous waveform (FMCW) Ambiguity function Linear FM Pulse Waveform - Gaussian Envelope (real part, pulse 1) Time (s) x Fast Time Sequences Using Staggered PRFs Before MTI filter After MTI filter Range (m) 12

13 System-Level Block Diagram Waveform Generator Transmitter Environment, Targets, and Interference Signal Processing Receiver 13

14 Transmitter Transmitter Gain Peak power Loss factor Monostatic and multistatic configurations Transmitter Radiators (transmit antennas) Narrowband signals Platform motion Radiators Transmit array = group of radiators Environment 14

15 RG (K) Receiver Collectors (receive antennas) Narrowband and wideband signals Plane and custom wavefront models Array shading Platform motion Receive array = group of collectors Environment Collectors Receiver characteristics Gain Loss factor Noise figure Reference temperature Monostatic and multistatic configurations Receiver Characteristics Chan (M) 15

16 System-Level Block Diagram Waveform Generator Transmitter Environment, Targets, and Interference Signal Processing Receiver 16

17 Environment, Targets, and Interference Environment model Free space Constant gamma clutter Barrage jammer Target Environment Target models Point target Swerling models Platform motion Polarization Interference 17

18 RG (K) System-Level Block Diagram Waveform Generator Transmitter Environment, Targets, and Interference Signal Processing Receiver Chan (M) 19

19 Temporal Processing Time varying gain control Power (dbw) Pulse compression and stretch processing Coherent, non-coherent integration Detection Constant false alarm rate (CFAR) ROC curves Neyman-Pearson detector threshold Albersheim and Shnidman equations Range and Doppler estimation P d Target Range Estimation Time (ms) NonfluctuatingCoherent Receiver Operating Characteristic (ROC) Curves SNR=13dB SNR=10dB SNR=3dB SNR=0dB P fa 20

20 Spatial Processing Digital beamforming Narrowband Conventional MVDR (Capon) LCMV Broadband Frost Time delay Time delay LCMV Subband phase shift Direction of arrival Uniform Arrays Sum and difference monopulse Beamscan, MVDR (Capon) Conformal arrays Beamscan, MVDR (Capon) 21

21 Magnitude Normalized Doppler Frequency Power (db) Magnitude Normalized Doppler Frequency Power (db) Space-Time Adaptive Processing (STAP) Displaced phase center array (DPCA) Adaptive DPCA Sample matrix inversion (SMI) Angle-Doppler response Signals collected by the ULA within the first pulse interval 0.5 Data Snapshot Angle Doppler Response Target Range (m) 1.5 x 10-6 SMI output Angle (degrees) SMI Weights Angle Doppler Response Target Range (m) Angle (degrees) 22

22 Example: Simulate End-to-End Radar System A complete end-to-end monostatic radar system Single element transmitter and 3-element array receiver Multiple targets with various speeds and positions 23

23 System Design Specification Probability of detection P d = 0.9 Probability of false alarm P fa = 1e-6 Maximum range R max = 5000 m Range resolution DR = 50 m Center frequency f c = 1 GHz Targets model non-fluctuating 24

24 Summary: Design and Simulate Pulse Radar Build the executable specification Develop detection algorithms Validate performance and compliance Refine component specifications at the system level 25

25 Outline Challenges in Radar System Design Modeling Pulse Radar System Modeling FMCW Radar System Designing Phased Array Integrating and Prototyping Radar System 26

26 FMCW Radars Applications Emerging trends Automotive: Adaptive cruise control Parking sensors Traffic control and more: Weather radar Military security (through-wall sensing, concealed weapon detection) Tank level gauging 27

27 FMCW Radar for Automotive The received signal is a delayed copy of the transmitted signal Car+Radar Target Ultra-large signal bandwidth (>100MHz) Ultra high frequencies (>77GHz) 28

28 What Behavior Can Be Modeled? Waveform Design Channel model (interference, target, noise) Antenna arrays (size, geometry) DSP RF Impairments (noise, non-linearity, frequency dependency) Algorithms for Data Analysis 29

29 Which MathWorks Tools Can Help? Phased Array System Toolbox Waveform design Array design Radar equation Channel model Detection algorithms SimRF Component noise Component Non-linearity Carrier frequency selectivity 30

30 Summary: Design and Simulate FMCW Radar Build the executable specification Develop detection algorithms Validate performance and compliance Refine component specifications at the system level 31

31 Outline Challenges in Radar System Design Modeling Pulse Radar System Modeling FMCW Radar System Designing Phased Array Integrating and Prototyping Radar System 32

32 Phased Array Design Geometry, layout, and element definition Array geometry Uniform array (linear, rectangular) Arbitrary geometry (conformal) Array layout Number of elements Element spacing Array shading/tapering Subarray Element definition Directionality (Isotropic, cosine-weighted, user specified) Heterogeneous array Polarization 33

33 Phased Array Analysis and Visualization Array directivity Grating lobe diagram Delay between elements Steering vector Non-ideal array 34

34 Demo: Complex Array Design and Visualization Arrays and subarrays with complex geometries Interactive 3D visualization 35

35 More Examples Phased Array Gallery 36

36 Outline Challenges in Radar System Design Modeling Pulse Radar System Modeling FMCW Radar System Designing Phased Array Integrating and Prototyping Radar System 37

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38 Generate Code for Your Radar Algorithms Deploy and execute on desktop Integrate into larger C/C++ based simulations Target embedded processors or FPGA iterate Algorithm Design and Code Generation in MATLAB verify / accelerate 39

39 Test Algorithms in Corporate Simulators Generate standalone C/C++ code Integrate C code into existing test harness Run tests in corporate simulator Tools MATLAB Coder Simulink Coder 40

40 More Information Product Manager: John Zhao Technical Presentations: Radar System Design and Analysis with MATLAB Design and Verify RF Transceivers for Radar Systems html Product Examples Phased Array System Toolbox 41