Radar Network Waveform Design for Target Tracking

Fuente: arXiv
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Hauptverfasser: Fan, Tao, Aubry, Augusto, De Maio, Antonio, Pallotta, Luca, Yu, Xianxiang, Cui, Guolong
Format: Preprint
Veröffentlicht: 2025
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author Fan, Tao
Aubry, Augusto
De Maio, Antonio
Pallotta, Luca
Yu, Xianxiang
Cui, Guolong
author_facet Fan, Tao
Aubry, Augusto
De Maio, Antonio
Pallotta, Luca
Yu, Xianxiang
Cui, Guolong
contents This paper addresses the synthesis of slow-time coded waveforms for single target tracking in a radar network operating under colored Gaussian interference. Based on the Posterior Cramér Rao Lower Bound (PCRLB), which characterizes the theoretically optimal accuracy of target state estimation, the problem at each tracking frame is formulated as the minimization of the trace of the PCRLB, together with power budget requirements and a similarity constraint to account for transmitter limitations and appropriate waveform features. To tackle this challenging optimization problem, an approximation solution technique is proposed, aimed at better tracking accuracy than the reference code. The resulting approximated problems, endowed with more tractable objective functions through Taylor-series expansion, are solved using a customized block Majorization-Minimization (block-MM) algorithm. The convergence properties of the developed procedure are thoroughly analyzed. Numerical results illustrate the accuracy improvements in the target state estimation process, and robust tracking performance under uncertain target state conditions achieved by the proposed technique.
format Preprint
id arxiv_https___arxiv_org_abs_2512_05757
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Radar Network Waveform Design for Target Tracking
Fan, Tao
Aubry, Augusto
De Maio, Antonio
Pallotta, Luca
Yu, Xianxiang
Cui, Guolong
Signal Processing
This paper addresses the synthesis of slow-time coded waveforms for single target tracking in a radar network operating under colored Gaussian interference. Based on the Posterior Cramér Rao Lower Bound (PCRLB), which characterizes the theoretically optimal accuracy of target state estimation, the problem at each tracking frame is formulated as the minimization of the trace of the PCRLB, together with power budget requirements and a similarity constraint to account for transmitter limitations and appropriate waveform features. To tackle this challenging optimization problem, an approximation solution technique is proposed, aimed at better tracking accuracy than the reference code. The resulting approximated problems, endowed with more tractable objective functions through Taylor-series expansion, are solved using a customized block Majorization-Minimization (block-MM) algorithm. The convergence properties of the developed procedure are thoroughly analyzed. Numerical results illustrate the accuracy improvements in the target state estimation process, and robust tracking performance under uncertain target state conditions achieved by the proposed technique.
title Radar Network Waveform Design for Target Tracking
topic Signal Processing
url https://arxiv.org/abs/2512.05757