基于两步最小二乘定位的偏差改进算法

doi:10.7527/S1000-6893.2015.0182

Abstract

Abstract:

Bias of a source location estimate using classical least square(LS) algorithm is significant when the noise is large. This paper started by deriving the theoretical bias of the time-differences-of-arrival(TDOA) and angle-of-arrival(AOA) positioning which used the classical two-step LS algorithm and found the reason which caused the bias. Then the improved TDOA and AOA algorithm was proposed by adding the quadratic constraints to the expectation of the error. Compared to other methods with constraints, the novel algorithm can reduce the bias considerably. Furthermore, because the new algorithm does not require eigenvalue decomposition and can obtain the closed-form solution, it has little computation load. Simulation shows that the new method can reduce the bias significantly and obtain the original mean-square error(MSE). The improved algorithm is able to lower the bias to the same level as the maximum likelihood estimator.

Key words: multi-station passive localization, bias estimate, weighted least square, TDOA and AOA jointed localization, mean-square error

CLC Number:

ZHANG Jie, JIANG Jianzhong, GUO Junli. Improved bias algorithm for localization using two-step least square[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2016, 37(2): 695-705.

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Improved bias algorithm for localization using two-step least square

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