{"title":"抑制干扰下多目标定位MIMO雷达动态收发波束优化","authors":"Jun Sun;Wei Yi;Ye Yuan;Pramod K. Varshney","doi":"10.1109/TSP.2025.3572503","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a dynamic transmit and receive beampattern optimization (DTRBO) method for colocated MIMO (C-MIMO) radars in cognitive multi-target tracking (MTT) scenarios under suppression jamming. To accurately account for the effects of suppression jamming on MTT performance, we develop a comprehensive signal model that integrates the complete transmit-receive beamforming process into the resource optimization framework. Based on this enhanced signal model, we derive an enumeration-based posterior Cramér-Rao lower bound (PCRLB), which incorporates both measurement errors and target miss detections, providing a more accurate performance metric under suppression jamming. Using the derived PCRLB, the DTRBO strategy is formulated to dynamically optimize transmit and receive beams for each tracking interval, thereby maximizing global MTT performance. Due to the coupling of optimization variables and the non-convexity of the derived PCRLB, the resulting optimization problem is computationally challenging. To address this, we propose a partition-based three-stage iterative method to decouple the variables, employing a first-order Taylor expansion-based convex approximation technique to solve the non-convex problem efficiently. Simulation results demonstrate the effectiveness and the superiority of the proposed DTRBO strategy in terms of both MTT performance and anti-jamming capabilities, outperforming existing approaches that omit the beampattern modeling process in resource-aware optimization.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"2271-2287"},"PeriodicalIF":4.6000,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic Transmit-Receive Beampattern Optimization of Colocated MIMO Radars for Multi-Target Tracking Under Suppression Jamming\",\"authors\":\"Jun Sun;Wei Yi;Ye Yuan;Pramod K. Varshney\",\"doi\":\"10.1109/TSP.2025.3572503\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a dynamic transmit and receive beampattern optimization (DTRBO) method for colocated MIMO (C-MIMO) radars in cognitive multi-target tracking (MTT) scenarios under suppression jamming. To accurately account for the effects of suppression jamming on MTT performance, we develop a comprehensive signal model that integrates the complete transmit-receive beamforming process into the resource optimization framework. Based on this enhanced signal model, we derive an enumeration-based posterior Cramér-Rao lower bound (PCRLB), which incorporates both measurement errors and target miss detections, providing a more accurate performance metric under suppression jamming. Using the derived PCRLB, the DTRBO strategy is formulated to dynamically optimize transmit and receive beams for each tracking interval, thereby maximizing global MTT performance. Due to the coupling of optimization variables and the non-convexity of the derived PCRLB, the resulting optimization problem is computationally challenging. To address this, we propose a partition-based three-stage iterative method to decouple the variables, employing a first-order Taylor expansion-based convex approximation technique to solve the non-convex problem efficiently. Simulation results demonstrate the effectiveness and the superiority of the proposed DTRBO strategy in terms of both MTT performance and anti-jamming capabilities, outperforming existing approaches that omit the beampattern modeling process in resource-aware optimization.\",\"PeriodicalId\":13330,\"journal\":{\"name\":\"IEEE Transactions on Signal Processing\",\"volume\":\"73 \",\"pages\":\"2271-2287\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Signal Processing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11012914/\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/11012914/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Dynamic Transmit-Receive Beampattern Optimization of Colocated MIMO Radars for Multi-Target Tracking Under Suppression Jamming
In this paper, we propose a dynamic transmit and receive beampattern optimization (DTRBO) method for colocated MIMO (C-MIMO) radars in cognitive multi-target tracking (MTT) scenarios under suppression jamming. To accurately account for the effects of suppression jamming on MTT performance, we develop a comprehensive signal model that integrates the complete transmit-receive beamforming process into the resource optimization framework. Based on this enhanced signal model, we derive an enumeration-based posterior Cramér-Rao lower bound (PCRLB), which incorporates both measurement errors and target miss detections, providing a more accurate performance metric under suppression jamming. Using the derived PCRLB, the DTRBO strategy is formulated to dynamically optimize transmit and receive beams for each tracking interval, thereby maximizing global MTT performance. Due to the coupling of optimization variables and the non-convexity of the derived PCRLB, the resulting optimization problem is computationally challenging. To address this, we propose a partition-based three-stage iterative method to decouple the variables, employing a first-order Taylor expansion-based convex approximation technique to solve the non-convex problem efficiently. Simulation results demonstrate the effectiveness and the superiority of the proposed DTRBO strategy in terms of both MTT performance and anti-jamming capabilities, outperforming existing approaches that omit the beampattern modeling process in resource-aware optimization.
期刊介绍:
The IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals. The term “signal” includes, among others, audio, video, speech, image, communication, geophysical, sonar, radar, medical and musical signals. Examples of topics of interest include, but are not limited to, information processing and the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals.