Research and Development Department, Sichuan Institute of Aerospace Electronics of China, No. 105, Yiduzhong Road, Chengdu 610100, China.
School of Information and Communication Engineering, University of Electronic Science and Technology of China, No.2006, Xiyuan Avenue, West Hi-tech Zone, Chengdu 611731, China.
Sensors (Basel). 2019 Mar 3;19(5):1084. doi: 10.3390/s19051084.
Detecting unresolved targets is very important for radars in their target tracking phase. For wideband radars, the unresolved target detection algorithm should be fast and adaptive to different bandwidths. To meet the requirements, a detection algorithm for wideband monopulse radars is proposed, which can detect unresolved targets for each range profile sampling points. The algorithm introduces the Gaussian mixture model and uses a priori information to achieve high performance while keeping a low computational load, adaptive to different bandwidths. A comparison between the proposed algorithm and the latest unresolved target detection algorithm Joint Multiple Bin Processing Generalized Likelihood Ratio Test (JMBP GLRT) is carried out by simulation. On Rayleigh distributed echoes, the detection probability of the proposed algorithm is at most 0.5456 higher than the JMBP GLRT for different signal-to-noise ratios (SNRs), while the computation time of the proposed algorithm is no more than two 10,000ths of the JMBP GLRT computation time. On bimodal distributed echoes, the detection probability of the proposed algorithm is at most 0.7933 higher than the JMBP GLRT for different angular separations of two unresolved targets, while the computation time of the proposed algorithm is no more than one 10,000th of the JMBP GLRT computation time. To evaluate the performance of the proposed algorithm in a real wideband radar, an experiment on field test measured data was carried out, in which the proposed algorithm was compared with Blair GLRT. The results show that the proposed algorithm produces a higher detection probability and lower false alarm rate, and completes detections on a range profile within 0.22 ms.
检测未解析目标对于雷达在目标跟踪阶段非常重要。对于宽带雷达,未解析目标检测算法应快速且适应不同带宽。为满足要求,提出了一种宽带单脉冲雷达的检测算法,该算法可以针对每个距离剖面采样点检测未解析目标。该算法引入了高斯混合模型,并利用先验信息实现了高性能,同时保持了低计算负载,适应不同带宽。通过仿真对所提出的算法与最新的未解析目标检测算法联合多-bin 处理广义似然比检验(JMBP GLRT)进行了比较。在瑞利分布回波上,对于不同信噪比(SNR),所提出的算法的检测概率比 JMBP GLRT 最多高 0.5456,而所提出的算法的计算时间不超过 JMBP GLRT 计算时间的两万分之一。在双模态分布回波上,对于两个未解析目标的角分离不同,所提出的算法的检测概率比 JMBP GLRT 最多高 0.7933,而所提出的算法的计算时间不超过 JMBP GLRT 计算时间的一万分之一。为了评估所提出的算法在实际宽带雷达中的性能,进行了现场测试测量数据的实验,其中将所提出的算法与 Blair GLRT 进行了比较。结果表明,所提出的算法产生了更高的检测概率和更低的虚警率,并且在 0.22ms 内完成了距离剖面上的检测。