In this paper, a passive multiple-input multiple-output (MIMO) radar system with widely separated antennas that estimates the positions and velocities of multiple moving targets by utilizing time delay (TD) and doppler shift (DS) measurements is proposed. Passive radar systems can detect targets by using multiple uncoordinated and un-synchronized illuminators and we assume that all the measurements including TD and DS have been known by a preprocessing method. In this study, the algorithm can be divided into three stages. First, based on location information within a certain range and utilizing the DBSCAN cluster algorithm we can obtain the initial position of each target. In the second stage according to the correlation between the TD measurements of each target in a specific receiver and the DSs, we can find the set of DS measurements for each target. Therefore, the initial speed estimated values can be obtained employing the least squares (LS) method. Finally, maximum likelihood (ML) estimation of a first-order Taylor expansion joint TD and DS is applied for a better solution. Extensive simulations show that the proposed algorithm has a good estimation performance and can achieve the Cramér-Rao lower bound (CRLB) under the condition of moderate measurement errors.

We consider the Doppler ambiguity compensation problem for weak moving target detection in passive bistatic radar. Detecting an unknown high-speed weak target has a high probability of the presence of Doppler ambiguity, which will decrease the integration performance and accordingly make the target detection difficult under low signal-to-noise ratio (SNR) environments. Resorting to the well-known keystone transform (KT) method, an approach to compensate for the Doppler ambiguity within the batch is proposed for the first time. The proposed approach establishes a good coupling between the reference and echo signals by adding a frequency shift related to the Doppler frequency in the procedure of computing the cross ambiguity function (CAF). Simulation results show that the coherent integration gain of our approach is close to the theoretical upper bound even in the presence of Doppler ambiguity.