基于动态规划的非均匀杂波环境中的复似然比检测前跟踪算法

A Dynamic Programming Track-Before-Detect Algorithm Using a Complex Likelihood Ratio Function for Applications in Inhomogeneous Clutter Conditions

非均匀杂波背景下的微弱目标检测是一个具有挑战性的难题,而基于动态规划的检测前跟踪算法是一种检测微弱目标的高效算法,然而杂波的非均匀性是影响该算法检测性能的重要因素。本文提出了一种将动态规划算法与先验杂波图信息相结合的新算法。然而现存的文献在构造动态规划的值函数时仅仅利用了复数据的幅度信息。针对以上缺点,本文提出了一种将杂波图与复数据相位信息相结合的复似然比函数,然后利用该似然比函数作为动态规划的值函数对目标进行检测和跟踪,最后对伪航迹进行了有效处理。仿真表明了该算法的可行性和高效性。

Detection of dim targets in inhomogeneous clutter is a challenging task.The track-before-detect(TBD)algorithm based on dynamic programming(DP)is an effective method for detecting dim targets.However,the performance of DP TBD algorithms is greatly degraded by inhomogeneous clutter conditions.A novel algorithm which combines DP algorithm with prior clutter-map information is proposed in this paper to improve the detection of dim targets in inhomogeneous clutter.In addition,only amplitude information of complex data is used in constructing merit functions for DP algorithms according to available research papers.This paper proposes a complex likelihood ratio function that combines clutter-map information with phase information of complex data.The proposed complex likelihood ratio function is used as the merit function of the DP algorithm.Finally,the false track problem is solved effectively.The simulation results prove the feasibility and high efficiency of the proposed algorithm.