摘要
由于现有雷达目标跟踪波形和检测门限自适应算法大多围绕以距离、距离率作为量测的一维运动目标展开,忽略了角度对目标跟踪的影响,从而无法对目标进行跟踪定位。为此,提出一种杂波背景下针对二维机动目标跟踪的雷达波形和检测门限联合自适应算法。首先,对传统基于时延-多普勒分辨单元的理论作进一步扩展,设计出一种包含距离-距离率和方位为量测的具有“棱柱”结构的分辨单元;然后,给出了包含波形参数和检测门限的量测误差协方差的联合近似表达式;最后,利用认知雷达思想,以滤波误差协方差的迹最小为代价函数自适应选择下一时刻的波形参数和检测门限,以提高系统的跟踪性能。仿真结果表明,波形和检测门限联合自适应算法的跟踪性能要明显优于传统的固定参数跟踪算法。
The existing adaptive waveform and detection threshold algorithms for radar target tracking focus mostly on the one-dimensional target with the range and range rate as measurements. As it ignores the effect of the angle on target tracking, it is impossible to track and locate the target. A joint adaptive waveform and detection threshold algorithm for two-dimensional maneuvering target tracking in clutter background is proposed. First, the traditional theory based on the time delay-Doppler resolution cell is further extended to design a resolution cell with the “prism” structure, which includes the range-range rate and azimuth measurements. Then, an approximate joint expression for measurement error covariance, containing the waveform parameter and detection threshold, is given. Finally, inspired by the cognitive radar, the next waveform parameters and detection threshold are adaptively selected at the cost of minimizing the trace of filtering error covariance to improve the tracking performance of the system. Simulation results show that the performance of the waveform and detection threshold self-adaption algorithm is obviously superior to the fixed parameter algorithm.
作者
王树亮
毕大平
阮怀林
WANG Shuliang;BI Daping;RUAN Huailin(College of Electronic Engineering,National University of Defence Technology,Hefei 230037,China)
出处
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
2019年第3期96-101,共6页
Journal of Xidian University
基金
国家自然科学基金(61671453)
安徽省自然科学基金(1608085MF123)
关键词
认知雷达
联合检测跟踪
分辨单元
波形选择
检测门限自适应
cognitive radar
joint detection-tracking
resolution cell
waveform selection
adaptive detection threshold
