Approximate Maximum Likelihood Algorithm for Moving Source Localization Using TDOA and FDOA Measurements

作者：Yu Huagang^*; Huang Gaoming; Gao Jun; Wu Xinhui

来源：Chinese Journal of Aeronautics, 2012, 25(4): 593-597.

DOI：10.1016/S1000-9361(11)60423-8

• approximate maximum likelihood (AML)
• maximum likelihood (ML)
• source localization
• time differences of arrival (TDOA)
• frequency differences of arrival (FDOA)

A closed-form approximate maximum likelihood (AML) algorithm for estimating the position and velocity of a moving source is proposed by utilizing the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements of a signal received at a number of receivers. The maximum likelihood (ML) technique is a powerful tool to solve this problem. But a direct approach that uses the ML estimator to solve the localization problem is exhaustive search in the solution space, and it is very computationally expensive, and prohibits real-time processing. On the basis of ML function, a closed-form approximate solution to the ML equations can be obtained, which can allow real-time implementation as well as global convergence. Simulation results show that the proposed estimator achieves better performance than the two-step weighted least squares (WLS) approach, which makes it possible to attain the Cramer-Rao lower bound (CRLB) at a sufficiently high noise level before the threshold effect occurs.

• 出版日期2012-8
• 单位中国人民解放军海军工程大学