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Direction-of-arrival (DOA) estimation has been an important research topic in the field of radar signal processing for a long time. Recently, joint estimation of DOA and frequency has been extensively studied. This paper considers joint DOA and frequency estimation of multiple narrow-band signals received by array radars at sub-Nyquist rates. A new sub-Nyquist array architecture (a sparse array radar whose the reference unit connects to a sparse multi-coset structure and the other units connect to 2 channel multi-coset structure) and corresponding efficient technique (a joint estimation algorithm with an augmenting method) are proposed. The estimation algorithm can match frequencies up with corresponding DOAs, and the augmenting method can increase the capability of the number of identifiable signals from $M-1$ to $Q-1(Q$ is extended estimating degrees of freedom). We further analyze the minimum total sampling rate of achieving joint estimation. Simulations results verify the effectiveness and performance of this technique in this sparse array structure.

In this work, the terrain data is exploited for passive source localization with Doppler frequency shift (DFS) measurements. The localization problem is modeled as a maximum likelihood estimation (MLE) problem. Firstly, in order to avoid carrying out optimization step on a highly nonlinear objective function, the likelihood function is reformulated as a constrained weighted least squares (CWLS) problem. Then it is further relaxed into the semidefinite programming (SDP) problem by a semidefinite relaxation (SDR) method, which can be solved by modern convex optimization methods. By incorporating the terrain data, the localization accuracy is promoted. The performance of the proposed algorithm is examined via simulations in a typical scenario.

This paper addresses the problem of target detection and tracking through a single frequency network with receiver position error. We consider the case that the SNR is low and it is hard to detect a target using the common detection algorithm like CFAR. The particle filter based track-before-detect algorithm is adopted to integrate the signal through sampling intervals to increase the SNR. The receiver is registered along with target detection and tracking. The performance of proposed algorithm is examined through simulations.

In this work, a stationary target localization based on differential received signal strength in the presence of location errors is presented. In the proposed algorithm, it is considered that the exact position of the receivers are not available. By taking both the measurements and location errors into account, according to the Constrained Weighted Least Squares (CWLS) criterion, the Differential Received Signal Strength (DRSS) measurements are formulated as a form that is related to the target position. However, due to the non-convex nature of the CWLS problem, it is difficult to obtain the globally solution. Then the semidefinite relaxation (SDR) technique is applied to relax the CWLS problem into a Semidefinite Programming Problem (SDP), which can be efficiently solved by some convex optimization algorithms. By comparing with the method which without considering the location errors, the proposed one is able to provide a more accurate estimation. The performance of the proposed algorithm is examined by simulation results.

This paper presents a novel structure of the GPS microstrip antenna, the working frequency of the antenna is GPS L1 band (at 1.575 GHz). The top-level patch of the antenna is an irregular shape, this shape is a centre of symmetry, and the purpose of such a design is in order to reduce the size of the antenna under the premise does not affect the antenna performance. Use ANSOFT HFSS simulation software to perform the simulation, the results show that the antenna was able to meet the requirements of the navigation satellite signals.