基于高程补偿的BLUE算法在塔康中的应用研究

基于塔康系统的斜距、方位和高程可对目标定位,但较大的量测误差影响定位精度。为提高估计精度,研究塔康中最佳线性无偏估计(best linear unbiased estimation, BLUE)滤波器的实现。建立地面站对目标的量测模型,并分析量测转换误差特性,推导出对应的BLUE滤波模型;针对目标从地面站上空过顶时出现无效量测的问题,通过对高程量测补偿的方法予以克服,解决传统算法在强非线性量测下误差较大的弊病。与经典方法的性能对比表明,改进算法有效地抑制了强非线性量测下的滤波发散,有很强的鲁棒性和实时性。

Application research of altitude compensation based BLUE algorithm in TACAN

Target position can be located with tactical air navigation (TACAN) system’s range, azimuth and altitude measurements, but the location precision is unfavorable because of large measurement errors. For the purpose of decreasing location errors, the implementation of the best linear unbiased estimator (BLUE) filter in the TACAN system is investigated. After building the measurement model of target positioning and analyzing the statistics characteristic of converted measurement errors, a corresponding BLUE filter model is derived. To circumvent the possible occurrence of invalid measurements, an altitude compensation technique is proposed to decrease estimation errors in strong nonlinearity cases. Simulation comparisons with other classical algorithms show the adaptive BLUE filter can solve the measurement ineffectiveness problem and overcome filter divergence effectively for short range target tracking, thus proving its superiority over others in robustness and efficiency.