基于OTHR与纯角度传感器群数据关联的模式辨识与定位精度提升

 天波超视距雷达(OTHR)目标跟踪面临着"三低"(低检测概率、低数据率和低测量精度)和"多径"(多条传播路径)的挑战,因此传播模式的准确辨识与目标定位精度提升是改善跟踪能力的关键。首先利用纯角度传感器群获得目标地理位置的初步估计,然后采用极大似然估计建立了OTHR的传播模式和杂波模式的辨识规则,进而利用最小方差估计准则实现OTHR和纯角度传感器群的量测融合。仿真结果表明,此算法的模式辨识正确率很高,能明显提升方位角的测量精度,但是不能明显提升径向距的精度。

Mode Identification and Location Improvement Based on Data Association of OTHR and Azimuth-only Sensors

Target tracking of over-the-horizon radar(OTHR) faces the challenge of low detection probability,low sampling rate,low measurement precision and multipath propagation.Identification of propagation modes and improvement of target location accuracy will significantly affect both data association and estimate updating,and thus they become the key concern on OTHR target tracking.In this paper,a scheme of measurement fusion of OTHR and azimuth-only sensors is presented to identify propagation/clutter modes and improve location accuracy.Measurements of azimuth-only sensors are first fused to obtain the preliminary estimates of location position via the standard least square method.Then,based on the above position estimate and OTHR measurements,a maximum-likelihood-estimation-based data association rule is proposed to identify the propagation modes and clutter mode.Finally,a minimum variance estimation method is given to improve the estimate of target position by fusing the associated data from OTHR and azimuth-only sensors.In simulation,it is found that the identification of propagation/clutter modes is satisfactory,and there is significant improvement on azimuth.However, the method does not result in significant improvement in the accuracy of geographical distance from the OTHR receiver to the target.