Hao Jiao;Junkun Yan;Wenqiang Pu;Tiancheng Li;Lin Ma;Hongwei Liu
{"title":"复杂目标环境下相控阵雷达异构时间资源安排与精细跟踪","authors":"Hao Jiao;Junkun Yan;Wenqiang Pu;Tiancheng Li;Lin Ma;Hongwei Liu","doi":"10.1109/TSP.2025.3599241","DOIUrl":null,"url":null,"abstract":"Complex target environments present characteristics of saturation, high speed, and high maneuverability, posing increasingly challenging demands for target tracking. In this context, traditional phased-array radar (PAR) faces the dilemma of limited tracking resources and filter model mismatch. To address these issues, this paper proposes a heterogeneous time resource arrangement (HTRA) and refined tracking (RT) method. Firstly, to mitigate the impact of maneuvering model mismatch, we modify the traditional strong tracking filter by considering the effect of different measurements on the correction of the maneuvering model, and formulate the RT method as an optimization problem according to the residual consistency criterion. Then, to properly allocate and arrange limited time resources, by defining a multidimensional time resource vector, we adopt the posterior estimate covariance from RT as a performance metric, and design a performance-driven HTRA framework to achieve time assignment under model mismatch conditions. Simulation results demonstrate that, compared to traditional approaches, the joint HTRA and RT strategy significantly enhance the tracking performance of complex targets within a given time resource budget.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"3362-3377"},"PeriodicalIF":5.8000,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Heterogeneous Time Resource Arrangement and Refined Tracking for Phased Array Radar Within Complex Target Environment\",\"authors\":\"Hao Jiao;Junkun Yan;Wenqiang Pu;Tiancheng Li;Lin Ma;Hongwei Liu\",\"doi\":\"10.1109/TSP.2025.3599241\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Complex target environments present characteristics of saturation, high speed, and high maneuverability, posing increasingly challenging demands for target tracking. In this context, traditional phased-array radar (PAR) faces the dilemma of limited tracking resources and filter model mismatch. To address these issues, this paper proposes a heterogeneous time resource arrangement (HTRA) and refined tracking (RT) method. Firstly, to mitigate the impact of maneuvering model mismatch, we modify the traditional strong tracking filter by considering the effect of different measurements on the correction of the maneuvering model, and formulate the RT method as an optimization problem according to the residual consistency criterion. Then, to properly allocate and arrange limited time resources, by defining a multidimensional time resource vector, we adopt the posterior estimate covariance from RT as a performance metric, and design a performance-driven HTRA framework to achieve time assignment under model mismatch conditions. Simulation results demonstrate that, compared to traditional approaches, the joint HTRA and RT strategy significantly enhance the tracking performance of complex targets within a given time resource budget.\",\"PeriodicalId\":13330,\"journal\":{\"name\":\"IEEE Transactions on Signal Processing\",\"volume\":\"73 \",\"pages\":\"3362-3377\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2025-08-14\",\"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/11125834/\",\"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/11125834/","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}
Heterogeneous Time Resource Arrangement and Refined Tracking for Phased Array Radar Within Complex Target Environment
Complex target environments present characteristics of saturation, high speed, and high maneuverability, posing increasingly challenging demands for target tracking. In this context, traditional phased-array radar (PAR) faces the dilemma of limited tracking resources and filter model mismatch. To address these issues, this paper proposes a heterogeneous time resource arrangement (HTRA) and refined tracking (RT) method. Firstly, to mitigate the impact of maneuvering model mismatch, we modify the traditional strong tracking filter by considering the effect of different measurements on the correction of the maneuvering model, and formulate the RT method as an optimization problem according to the residual consistency criterion. Then, to properly allocate and arrange limited time resources, by defining a multidimensional time resource vector, we adopt the posterior estimate covariance from RT as a performance metric, and design a performance-driven HTRA framework to achieve time assignment under model mismatch conditions. Simulation results demonstrate that, compared to traditional approaches, the joint HTRA and RT strategy significantly enhance the tracking performance of complex targets within a given time resource budget.
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.