Maximum Likelihood TDOA-FDOA Estimator Using Markov Chain Monte Carlo Sampling

ZHAO Yongjun; ZHAO Yongsheng; ZHAO Chuang

doi:10.11999/JEIT160050

Volume 38 Issue 11

Dec. 2016

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Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(11): 2745-2752

ZHAO Yongjun, ZHAO Yongsheng, ZHAO Chuang. Maximum Likelihood TDOA-FDOA Estimator Using Markov Chain Monte Carlo Sampling[J]. Journal of Electronics & Information Technology, 2016, 38(11): 2745-2752. doi: 10.11999/JEIT160050

Citation:

ZHAO Yongjun, ZHAO Yongsheng, ZHAO Chuang. Maximum Likelihood TDOA-FDOA Estimator Using Markov Chain Monte Carlo Sampling[J]. Journal of Electronics & Information Technology, 2016, 38(11): 2745-2752. doi: 10.11999/JEIT160050

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Maximum Likelihood TDOA-FDOA Estimator Using Markov Chain Monte Carlo Sampling

doi: 10.11999/JEIT160050

Funds:

The National Natural Science Foundation of China (61401469, 41301481, 61501513), The National High Technology Research and Development Program of China (2012AA7031015)

Received Date: 2016-01-13
Rev Recd Date: 2016-06-08
Publish Date: 2016-11-19

Abstract

Abstract

This paper investigates 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, and Markov Chain Monte Carlo (MCMC) method is applied to finding the global maximum of likelihood function by generating the realizations of TDOA and FDOA. Unlike the Cross Ambiguity Function (CAF) algorithm or the Expectation Maximization (EM) algorithm, the proposed algorithm can also 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 for different SNR conditions with higher accuracy and lower computational complexity.
- Passive location,
- Time Difference Of Arrival (TDOA),
- Frequency Difference Of Arrival (FDOA),
- Joint estimation,
- Maximum Likelihood (ML),
- Markov Chain Monte Carlo (MCMC) method

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References(22)

References

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