Abstract:

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.