In the Wi-Fi passive target tracking technology

it is difficult to extract the target's reflected path signals due to direct path signals and noise effects. A passive target tracking technology based on Wi-Fi multi-dimensional parameter feature is proposed. This technology uses serial interference cancellation instead of all-zero initialization to complete multiple paths initialization including Arrival of Angle (AoA)

Time of Flight (ToF) and Doppler Frequency Shifts (DFS). And the Frequency Domain Space Alternating Generalized Expectation-maximization (FD-SAGE) algorithm is improved to make up for traditional algorithms shortcomings such as slow convergence speed and noise impact. In addition

a hybrid data association method based on the least-cost multi-path network is used to solve the problem of unable to effectively associate paths when there are different numbers of paths at different times. Meanwhile

the method uses the optimal match in a fixed time window as the correlation data at a certain time

which reduces the irreversible error caused by a subsequent association failure caused by the association error. Experimental results show that this paper can achieve an average tracking accuracy of 1.3m in a complex indoor environment.