In passive location systems on the ground, the judgment and location of multi-target is more challenging compared with the case of single target. In this paper, we propose a method for multi-target identification and location in an arbitrary structure with three base stations (BSs). First of all, we discuss the scene of multi-targets judgment based on geometric dilution of precision (GDOP) value. Secondly, we propose an algorithm that calculates the system coverage radius based on arbitrary three BS structures. The algorithm helps to identify the number of targets for unsupervised learning. Finally, we locate each target individually located again based on the linear constrained minimum variance (LCMV) beam former and time difference of arrival (TDOA) algorithm. In the simulations, we analyzed the location dispersion under different signal-to-noise ratio (SNR), then calculated the termination threshold of the k-means algorithm under different SNR. The simulation results show that, compared to the probability hypothesis density (PHD) filter and TDOA-angle-of-arrival (AOA) joint algorithm, the proposed method can increase more than 12.5% and 15.6% points. With the increase of the number of targets, the running time of our algorithm is controllable with better stability.