Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Sensors (Basel). 2018 Jul 12;18(7):2241. doi: 10.3390/s18072241.
This paper considers the detection of fluctuating targets in heavy-tailed clutter through the use of dynamic programming based on track-before-detect (DP⁻TBD) in radar systems. The clutter is modeled in terms of K-distribution, which can be widely used to describe non-Gaussian clutter received from high-resolution radars and radars working at small grazing angles. Swerling type 1 is considered to describe the target fluctuation between scans. Conventional TBD techniques suffer from significant performance loss in heavy-tailed environments due to the more frequent occurrences of target-like outliers. In this paper, we resort to a DP⁻TBD algorithm based on prior information, which can enhance the detection performance by using the environment and target fluctuating information during the integration process of TBD. Under non-Gaussian background, the expressions of the likelihood ratio merit function for Swerling type 1 targets are derived first. However, the closed-form of the merit function is difficult to obtain. In order to reduce the complexity of evaluating the merit function and the computational load, an efficient approximation method as well as a two-stage detection approach is proposed and used in the integration process. Finally, several numerical simulations of the new strategy and the comparisons are presented to verify that the proposed algorithm can improve the detection performance, especially for fluctuating targets in heavy-tailed clutter.
本文研究了在雷达系统中通过基于跟踪前检测（DP⁻TBD）的动态规划来检测重尾杂波中的脉动目标。杂波采用 K 分布进行建模，K 分布可以广泛用于描述高分辨率雷达和小掠射角雷达接收到的非高斯杂波。Swerling 1 型用于描述两次扫描之间的目标波动。由于目标似然的异常值更频繁地出现，传统的 TBD 技术在重尾环境下会遭受显著的性能损失。在本文中，我们采用基于先验信息的 DP⁻TBD 算法，通过在 TBD 的积分过程中利用环境和目标波动信息，来提高检测性能。在非高斯背景下，首先推导出 Swerling 1 型目标的似然比优势函数的表达式。然而，该优势函数的封闭形式很难获得。为了降低评估优势函数的复杂度和计算负载，提出并在积分过程中使用了一种有效的近似方法和两阶段检测方法。最后，对新策略进行了多次数值模拟和比较，验证了所提出的算法可以提高检测性能，特别是在重尾杂波中的脉动目标。
