Conventional multitarget tracking systems presume that each target produces at most one measurement per scan. Owing to the multiple ionosphere propagation paths in over‐the‐horizon radar, this assumption is not valid. To solve this problem, a novel multitarget tracking algorithm based on the finite set statistics (FISST), called multipath cardinality balanced multitarget multi‐Bernoulli (MP‐CBMeMBer) filter, is proposed in this study. First, the authors derive the MP‐CBMeMBer filter based on the FISST, and then both the sequential Monte Carlo and Gaussian mixture (GM) method are used to implement the proposed filter. Moreover, the extended Kalman filter is implemented to deal with the problem of the non‐linear measurement models for the GM‐MP‐CBMeMBer filter. Eventually, the simulation results are presented to demonstrate the effectiveness of the proposed filter.

In a passive radar system, the bearing of the target is difficult to measure for the signal‐to‐noise ratio of the target's echo signal is generally very low in practise. A novel method to estimate the echo signal's angle is proposed. The cross‐ambiguity function of direct‐path signal and each antenna's receiving signal is calculated to form a virtual array signal, in which the desired echo signal can be enhanced at a certain time delay and Doppler shift, so it is able to estimate its angle. We make the theoretical analysis about how the desired echo signal is enhanced. Some experimental results of an amplitude modulation (AM) radio‐based passive radar are presented to verify the effectiveness of the proposed method.

The direction-of-arrival (DOA) of the target’s echo signal is extremely important for passive detection and tracking. However, it is a challenge to estimate the echo signal’s DOA due to the low signal-to-noise ratio of the echo signal and the serious masking effect. In this paper, a novel method is developed to estimate the DOA of the echo signal through enhancing the desired echo signal and attenuating the interference in range-Doppler domain before performing the DOA estimation. Firstly, the cross-ambiguity functions of the direct path signal and the received array signal are calculated. Then, they are combined to form a single-snapshot virtual array signal. Under certain conditions, the desired echo signal can be enhanced and the interference can be attenuated simultaneously. After extending the single-snapshot virtual array signal to multi-snapshots, the conventional MUSIC approach can be performed, and the clutter interference can be suppressed significantly through subspace orthogonal meanwhile. Finally, the DOAs of echo signals, as well as their corresponding Doppler shifts can be measured on a two-dimensional direction-Doppler map. The virtual array signal’s construction principle and the gain of echo signal are analyzed theoretically, and some experimental results are presented to verify the effectiveness of the proposed method.

In a typical multipath propagation environment, there exists a strong direct path signal accompanying with several weak multipath signals. Due to the strong direct path interference and other masking effects, the Direction-of-Arrival (DOA) of a weak multipath signal is hard to be estimated. In this paper, a novel method is proposed to estimate the DOA of multipath signals with ultralow signal-to-noise ratio (SNR). The main idea is to increase the SNR and signal-to-interference ratio (SIR) of the desired multipath signal in time-delay domain before DOA estimation processing. Firstly, the cross-correlation functions of the direct path signal and the received array signal are calculated. Then, they are combined and constructed to an enhanced array signal. Under certain conditions, the SNR and SIR of the desired signal can be significantly increased. Finally, the DOAs of multipath signals can be estimated by conventional technologies, and the associated time delays can be measured on the DOA-time-shift map. The SNR and SIR gains of the desired signal are analyzed theoretically, and theoretical analysis also indicates that the Cramer–Rao bound can be reduced. Simulation examples are presented to verify the advantages of the proposed method.