基于径向速度检验的雷达网距离多假目标鉴别

Discrimination of Multi-Range-False-Target Jamming for Radar Network Based on Radial Velocity Testing

针对雷达网在鉴别距离多假目标干扰过程中,鉴别效果随距离多假目标密集程度增大而变差的问题,提出了一种基于目标径向速度估计的距离多假目标干扰鉴别方法。首先,选定基准雷达并进行量测分组预处理,将其他组网雷达目标量测转换至基准雷达局部坐标系下进行基于位置信息的量测关联,以初步排除不相关的虚假量测与杂波,同时减小计算量;然后,基于坐标转换后量测的位置信息估计出目标径向速度,与基准雷达径向速度量测进行检验,以实现虚假目标的鉴别。仿真结果表明,此方法在距离多假目标密集程度较大的情况下具有较高的正确鉴别率,且能够对目标进行稳定跟踪。

Considering that the effect of the multi-range-false-target deception jamming discrimination becoming worse as the intensive degree of multi-range-false-target increases, we proposed a method based on radial velocity estimation of radar network to discriminate the false target. Firstly, benchmark radar was selected and measurements were classified into groups for preprocessing, and the target measurements of other radars were transformed into the coordinate system of the benchmark radar for measurements association, thus to eliminate the false measurements and clutter as well as decrease the amount of computation. Then, the radial velocity of target was estimated by using the position information after coordinate transformation, which was then tested with the benchmark radar radial velocity for discriminating the false targets. Simulation results verified that proposed method can achieve high correct discrimination rate, and track the true target stably.