Waveform Optimization for Target Estimation by Cognitive Radar with Multiple Antennas

A new scheme based on Kalman filtering to optimize the waveforms of an adaptive multi-antenna radar system for target impulse response (TIR) estimation is presented. This work aims to improve the performance of TIR estimation by making use of the temporal correlation between successive received sign...

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Main Authors: Yu Yao, Junhui Zhao, Lenan Wu
Format: Article
Language:English
Published: MDPI AG 2018-05-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/18/6/1743
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author Yu Yao
Junhui Zhao
Lenan Wu
author_facet Yu Yao
Junhui Zhao
Lenan Wu
author_sort Yu Yao
collection DOAJ
description A new scheme based on Kalman filtering to optimize the waveforms of an adaptive multi-antenna radar system for target impulse response (TIR) estimation is presented. This work aims to improve the performance of TIR estimation by making use of the temporal correlation between successive received signals, and minimize the mean square error (MSE) of TIR estimation. The waveform design approach is based upon constant learning from the target feature at the receiver. Under the multiple antennas scenario, a dynamic feedback loop control system is established to real-time monitor the change in the target features extracted form received signals. The transmitter adapts its transmitted waveform to suit the time-invariant environment. Finally, the simulation results show that, as compared with the waveform design method based on the MAP criterion, the proposed waveform design algorithm is able to improve the performance of TIR estimation for extended targets with multiple iterations, and has a relatively lower level of complexity.
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spelling doaj.art-300b21c5b21b46c5bca588607042de0a2022-12-22T01:56:23ZengMDPI AGSensors1424-82202018-05-01186174310.3390/s18061743s18061743Waveform Optimization for Target Estimation by Cognitive Radar with Multiple AntennasYu Yao0Junhui Zhao1Lenan Wu2School of Information Engineering, East China Jiaotong University, Nanchang 330031, ChinaSchool of Information Engineering, East China Jiaotong University, Nanchang 330031, ChinaSchool of Information Science and Engineering, Southeast University, Nanjing 210096, ChinaA new scheme based on Kalman filtering to optimize the waveforms of an adaptive multi-antenna radar system for target impulse response (TIR) estimation is presented. This work aims to improve the performance of TIR estimation by making use of the temporal correlation between successive received signals, and minimize the mean square error (MSE) of TIR estimation. The waveform design approach is based upon constant learning from the target feature at the receiver. Under the multiple antennas scenario, a dynamic feedback loop control system is established to real-time monitor the change in the target features extracted form received signals. The transmitter adapts its transmitted waveform to suit the time-invariant environment. Finally, the simulation results show that, as compared with the waveform design method based on the MAP criterion, the proposed waveform design algorithm is able to improve the performance of TIR estimation for extended targets with multiple iterations, and has a relatively lower level of complexity.http://www.mdpi.com/1424-8220/18/6/1743cognitive radar systemKalman filteringtemporal correlated targetmultiple antennaswaveform optimization
spellingShingle Yu Yao
Junhui Zhao
Lenan Wu
Waveform Optimization for Target Estimation by Cognitive Radar with Multiple Antennas
Sensors
cognitive radar system
Kalman filtering
temporal correlated target
multiple antennas
waveform optimization
title Waveform Optimization for Target Estimation by Cognitive Radar with Multiple Antennas
title_full Waveform Optimization for Target Estimation by Cognitive Radar with Multiple Antennas
title_fullStr Waveform Optimization for Target Estimation by Cognitive Radar with Multiple Antennas
title_full_unstemmed Waveform Optimization for Target Estimation by Cognitive Radar with Multiple Antennas
title_short Waveform Optimization for Target Estimation by Cognitive Radar with Multiple Antennas
title_sort waveform optimization for target estimation by cognitive radar with multiple antennas
topic cognitive radar system
Kalman filtering
temporal correlated target
multiple antennas
waveform optimization
url http://www.mdpi.com/1424-8220/18/6/1743
work_keys_str_mv AT yuyao waveformoptimizationfortargetestimationbycognitiveradarwithmultipleantennas
AT junhuizhao waveformoptimizationfortargetestimationbycognitiveradarwithmultipleantennas
AT lenanwu waveformoptimizationfortargetestimationbycognitiveradarwithmultipleantennas