基于交叉定位和Hough变换检测前跟踪的水下目标检测方法

doi:10.12305/j.issn.1001-506X.2023.07.05

摘要/Abstract

摘要：

针对现代潜艇的低可探测性问题和隐蔽性探测需求, 提出了一种基于航空被动声纳浮标阵交叉定位和Hough变换检测前跟踪的水下微弱目标检测方法。首先, 构建基于线形浮标拦截阵的水下目标被动检测模型, 采用自适应关联的交叉定位方法, 获取目标位置信息, 实现了检测前数据预处理。然后, 采用点数积累和能量积累的双门限Hough检测方法, 得到了初始检测航迹。最后, 利用目标运动约束条件和航迹合并方法, 剔除虚假航迹及合并重复航迹, 提高了水下目标检测概率。仿真结果表明, 与时频检测方法相比较, 该方法在低信噪比条件下仍能保持较高的检测概率。

关键词: 水下目标, 被动声纳, 检测前跟踪, Hough变换, 双门限

Abstract:

Aiming at the low detectability and concealment detection requirements of modern submarines, an underwater weak target detection algorithm based on cross positioning of airborne passive sonar buoy array and Hough transform track-before-detect is proposed. Firstly, a passive detection model of underwater targets based on linear buoy interception array is constructed, and the cross-positioning method of adaptive correlation is used to obtain the target position information and realize data preprocessing before detection. Secondly, the initial detection track is obtained by adopting the double-threshold Hough transform method of point accumulation and energy accumulation. Finally, using target motion constraints and the track merging method, false tracks are eliminated and the duplicate tracks are merged to improve the detection probability of underwater targets. Simulation results show that compared with the time-frequency detection method, this method can still maintain a higher detection probability under the condition of low signal-to-noise ratio, and the error range of detection probability is smaller.

Key words: underwater target, passive sonar, track-before-detect, Hough transform, double-threshold

中图分类号:

TB566

王学敏, 张翔宇, 吴明辉, 李文海. 基于交叉定位和Hough变换检测前跟踪的水下目标检测方法[J]. 系统工程与电子技术, 2023, 45(7): 1957-1964.

Xuemin WANG, Xiangyu ZHANG, Minghui WU, Wenhai LI. Underwater target track-before-detect detection method based on cross location and Hough transform[J]. Systems Engineering and Electronics, 2023, 45(7): 1957-1964.

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信噪比/dB	检测概率/%			平均运行时间/s
信噪比/dB	WVD	WHT	本文方法	WVD	WHT	本文方法
5	67	77	80	25.7	35.1	37.2
10	72	83	83	23.6	23.6	23.8
15	78	86	85	23.3	23.4	23.3
20	80	88	89	22.1	22.1	22.2

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