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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2017, Vol. 38 ›› Issue (1): 319994-319994.doi: 10.7527/S1000-6893.2016.0085

• Electronics and Electrical Engineering and Control • Previous Articles     Next Articles

TDOA-FDOA joint estimation using importance sampling method

ZHAO Yongsheng, ZHAO Yongjun, ZHAO Chuang   

  1. School of Navigation and Aerospace Engineering, PLA Information Engineering University, Zhengzhou 450001, China
  • Received:2015-12-31 Revised:2016-03-15 Online:2017-01-15 Published:2016-03-21
  • Supported by:

    National Natural Science Foundation of China (61401469, 61501513); National High Technology Research and Development Program of China (2012AA7031015)

Abstract:

To solve the joint estimation of time difference of arrival (TDOA) and frequency difference of arrival (FDOA) in passive location system, where the true value of the reference signal is unknown, a novel maximum likelihood (ML) estimator of TDOA and FDOA is constructed. Then importance sampling (IS) method is applied to find the maximum of likelihood function by generating the samples of TDOA and FDOA. Unlike the cross ambiguity function (CAF) algorithm or the expectation maximization (EM) algorithm, the proposed algorithm can estimate the TDOA and FDOA of non-integer multiple of the sampling interval and has no dependence on the initial estimate. The Cramer Rao lower bound (CRLB) is also derived. Simulation results show that the proposed algorithm outperforms the CAF and EM algorithm with higher accuracy and moderate computational complexity, and approaches the CRLB for different SNR conditions.

Key words: time difference of arrival, frequency difference of arrival, joint estimation, maximum likelihood, importance sampling

CLC Number: