一种多基地雷达中多元量化融合算法

doi:10.3969/j.issn.1001-2400.2018.05.006

西安电子科技大学学报

一种多基地雷达中多元量化融合算法

曹鼎1,2，周生华1,2;刘宏伟1,2;邵志强1,2

(1. 西安电子科技大学雷达信号处理国家重点实验室，陕西西安 710071；
2. 西安电子科技大学信息感知技术协同创新中心，陕西西安 710071)

收稿日期:2017-11-19 出版日期:2018-10-20 发布日期:2018-09-25
作者简介:曹鼎(1988-), 男，西安电子科技大学博士研究生，E-mail：dingcao@xidian.edu.cn
基金资助:
国家自然科学基金资助项目(61401329, 61372134, 61501351)；国家杰出青年科学基金资助项目(61525105)

Fusion method based on multilevel quantization in multistatic radar

CAO Ding1,2;ZHOU Shenghua1,2;LIU Hongwei1,2;SHAO Zhiqiang1,2

(1. National Key Lab. of Radar Signal Processing, Xidian Univ., Xi'an 710071, China;
2. Collaborative Innovation Center of Information Sensing and Understanding, Xidian Univ., Xi'an 710071, China)

Received:2017-11-19 Online:2018-10-20 Published:2018-09-25

摘要/Abstract

摘要：

在多基地雷达系统中，为了满足通讯带宽限制，提出了一种基于置信域的最小方差量化器．根据各个局部雷达站原始观测的广义似然比确定一个连续的非置信区间，余下的判决空间为置信区间．利用最小方差量化器对非置信区间进行划分，以获得满足通讯带宽限制的量化器设计．最后将局部量化器的输出电频作为局部判决结果向融合中心传输，并利用非相参积累检测器获得全局判决．利用输出电频的概率质量函数，推导了全局虚警概率和检测概率．仿真结果表明，当量化位数为3bit时，可以获得趋近于分布式广义似然比检测算法的性能．

关键词: 多基地雷达, 多元量化器, 广义似然比

Abstract:

In multistatic radar, a confidence region-based least square quantizer is proposed to satisfy the communication constraints. The “non-confidence region” is a continuous interval in the decision space of the generalized likelihood ratio of raw observations, while the rest part is called the “confidence region”. The “non-confidence region” is partitioned through the least square quantizer according to the communication bandwidth. The outputs of the local quantizers, also termed quantization levels, are regarded as the local decisions to be transmitted to the fusion center, where a non-coherent integrator is utilized for further global decision making. Global probability of false alarm and probability of detection are derived through the probability mass functions of the quantization levels. Simulation results indicate that the detection performance with 3bit quantization can approach that of the distributed generalized likelihood ratio.

Key words: multistatic radars, multilevel quantizer, generalized likelihood ratio

曹鼎;周生华;刘宏伟;邵志强. 一种多基地雷达中多元量化融合算法[J]. 西安电子科技大学学报, 2018, 45(5): 32-37+49.

CAO Ding;ZHOU Shenghua;LIU Hongwei;SHAO Zhiqiang. Fusion method based on multilevel quantization in multistatic radar[J]. Journal of Xidian University, 2018, 45(5): 32-37+49.

参考文献［14］

［1］	ZHOU S H, LIU H W. Space-partition-based Target Detection for Distributed MIMO Radar［J］. IEEE Transactions on Aerospace and Electronic Systems, 2013, 49(4): 2717-2729.
［2］	VARSHNEY P K. Distributed Detection and Data Fusion［M］. New York: Springer, 1997: 1-5.
［3］	周生华, 刘宏伟, 刘保昌, 等. 信噪比加权空间分集雷达目标检测算法［J］. 西安电子科技大学学报, 2011, 38(4): 82-88.
	ZHOU Shenghua, LIU Hongwei, LIU Baochang, et al. SNR Weighting Based Target Detection Algorithm for Spatial Diversity Radar［J］. Journal of Xidian University, 2011, 38(4): 82-88.
［4］	ZHAO H Y, LIU J, ZHANG Z J, et al. Linear Fusion for Target Detection in Passive Multistatic Radar［J］. Signal Processing, 2017, 130: 175-182.
［5］	HELSTROM C W. Gradient Algorithm for Quantization Levels in Distributed Detection Systems［J］. IEEE Transactions on Aerospace and Electronic Systems, 1995, 31(1): 390-398.
［6］	GAO F, GUO L, LI H B, et al. Quantizer Design for Distributed GLRT Detection of Weak Signal in Wireless Sensor Networks［J］. IEEE Transactions on Wireless Communications, 2015, 14(4): 2032-2042.
［7］	ALTAY C, DELIC H. Optimal Quantization Intervals in Distributed Detection［J］. IEEE Transactions on Aerospace and Electronic Systems, 2016, 52(1): 38-48.
［8］	AZIZ A. A Soft-decision Fusion Approach for Multiple-sensor Distribution Binary Detection Systems［J］. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47(3): 2208-2216.
［9］	LLOYD S. Least Squares Quantization in PCM［J］. IEEE Transactions on Information Theory, 1982, 28(2): 129-137.
［10］	ZHOU S, LIU H. Signal Fusion-based Target Detection Algorithm for Spatial Diversity Radar［J］. IET Radar, Sonar and Navigation, 2011, 5(3): 204-214.
［11］	KELLY E J. An Adaptive Detection Algorithm［J］. IEEE Transactions on Aerospace and Electronic Systems, 1986, 22(1): 115-127.
［12］	胡勤振, 杨芊, 苏洪涛, 等. 分布式 MIMO雷达双门限GLRT CFAR检测［J］. 西安电子科技大学学报, 2016, 43(4): 29-33.
	HU Qinzhen, YANG Qian, SU Hongtao, et al. Double-threshold GLRT CFAR Detection in Distributed MIMO Radar［J］. Journal of Xidian University, 2016, 43(4): 29-33.
［13］	胡勤振, 苏洪涛, 周生华, 等. 多基地雷达中双门限 CFAR 检测算法［J］. 电子与信息学报, 2016, 28(10): 2430-2436.
	HU Qinzhen, SU Hongtao, ZHOU Shenghua, et al. Double Threshold CFAR Detection for Multisite Radar［J］. Journal of Electronics and Information Technology, 2016, 28(10): 2430-2436.
［14］	CAO D, ZHOU S H, LIU H W, et al. Signal Censoring and Fusing with System-level Communication Constraints in Multistatic Radar: a J-divergence and Bhattacharyya Distance Based Approach［J］. IET Radar, Sonar and Navigation, 2017, 11(12): 1802-1814.

[1]	赫彬,苏洪涛. 一种多目标与多基地雷达之间的博弈策略[J]. 西安电子科技大学学报, 2021, 48(2): 125-132.
[2]	李海鹏,冯大政,周永伟. 多基地雷达栅栏覆盖的优化布站方法[J]. 西安电子科技大学学报, 2021, 48(2): 147-155.
[3]	张彦飞,孙文杰,孙玉梅,孟祥伟,陈祥光. 非高斯杂波中机载多进多出雷达动目标检测[J]. 西安电子科技大学学报, 2020, 47(3): 23-31.
[4]	胡勤振;杨芊;苏洪涛;周生华;刘子威;杨阳. 分布式MIMO雷达双门限GLRT CFAR检测[J]. 西安电子科技大学学报, 2016, 43(4): 29-33+85.
[5]	严俊坤;夏双志;戴奉周;刘宏伟;保铮. 异步多基地雷达系统目标跟踪的功率分配算法[J]. J4, 2013, 40(6): 32-38+57.
[6]	许述文;水鹏朗. 一种提高距离扩展目标检测性能的新方法[J]. J4, 2010, 37(6): 1053-1058.
[7]	向新1;2;王勇1;易克初1;田红心1. 基于广义似然比检验的差分超宽带信号接收机 [J]. J4, 2007, 34(1): 26-284.
[8]	陈伯孝;孟佳美;张守宏. 岸-舰多基地地波超视距雷达的发射波形及其解调[J]. J4, 2005, 32(1): 7-11.
[9]	张良;保铮;廖桂生. 基于空时的自适应处理的恒虚警检测算法研究[J]. J4, 2000, 27(3): 265-270.
[10]	暂时无作者信息. 多基地雷达最佳定位算法[J]. J4, 1999, 26(4): 397-401.

一种多基地雷达中多元量化融合算法

Fusion method based on multilevel quantization in multistatic radar

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

参考文献［14］

相关文章 10

Metrics

本文评价

推荐阅读 10

一种多基地雷达中多元量化融合算法

Fusion method based on multilevel quantization in multistatic radar

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

参考文献 ［14］

相关文章 10

Metrics

本文评价

推荐阅读 10

参考文献［14］