Waveform Analysis and Optimization for Radar Coincidence Imaging with Modeling Error

RCI is a novel superresolution staring imaging technique based on the idea of wavefront modulation and temporal-spatial stochastic radiation field. For RCI, the reference matrix should be known accurately, and the imaging performance depends on the incoherence property of the reference matrix. Unfortunately, the modeling error, which degrades the performance significantly, exists generally. In this paper, RCI using frequency-hopping waveforms (FH-RCI) is considered, and a FH code design method aiming to increase the robustness of RCI to modeling error is proposed. First, we derive the upper bound of imaging error for RCI with modeling error and conclude that the condition number of the reference matrix determines the imaging performance. Then the object function for waveform design which minimizes the condition number of the reference matrix is achieved, and the quantum simulated annealing (QSA) is employed to optimize the FH code. Numerical simulations show that the optimized FH code could decrease the condition number of the reference matrix and improve the imaging performance of RCI with modeling error

Radar Coincidence Imaging for Off-Grid Target Using Frequency-Hopping Waveforms

Radar coincidence imaging (RCI) is a high-resolution staring imaging technique without the limitation of the target relative motion. To achieve better imaging performance, sparse reconstruction is commonly used. While its performance is based on the assumption that the scatterers are located at the prediscretized grid-cell centers, otherwise, off-grid emerges and the performance of RCI degrades significantly. In this paper, RCI using frequency-hopping (FH) waveforms is considered. The off-grid effects are analyzed, and the corresponding constrained Cramér-Rao bound (CCRB) is derived based on the mean square error (MSE) of the “oracle” estimator. For off-grid RCI, the process is composed of two stages: grid matching and off-grid error (OGE) calibration, where two-dimension (2D) band-excluded locally optimized orthogonal matching pursuit (BLOOMP) and alternating iteration minimization (AIM) algorithms are proposed, respectively. Unlike traditional sparse recovery methods, BLOOMP realizes the recovery in the refinement grids by overwhelming the shortages of coherent dictionary and is robust to noise and OGE. AIM calibration algorithm adaptively adjusts the OGE and, meanwhile, seeks the optimal target reconstruction result

Ultra Wideband

Ultra wideband (UWB) has advanced and merged as a technology, and many more people are aware of the potential for this exciting technology. The current UWB field is changing rapidly with new techniques and ideas where several issues are involved in developing the systems. Among UWB system design, the UWB RF transceiver and UWB antenna are the key components. Recently, a considerable amount of researches has been devoted to the development of the UWB RF transceiver and antenna for its enabling high data transmission rates and low power consumption. Our book attempts to present current and emerging trends in-research and development of UWB systems as well as future expectations

Joint Waveform and Clustering Design for Coordinated Multi-point DFRC Systems

To improve both sensing and communication performances, this paper proposes a coordinated multi-point (CoMP) transmission design for a dual-functional radar-communication (DFRC) system. In the proposed CoMP-DFRC system, the central processor (CP) coordinates multiple base stations (BSs) to transmit both the communication signal and the dedicated probing signal. The communication performance and the sensing performance are both evaluated by the signal-to-interference-plus-noise ratio (SINR). Given the limited backhaul capacity, we study the waveform and clustering design from both the radar-centric perspective and the communication-centric perspective. Dinkelbach’s transform is adopted to handle the single-ratio fractional objective for the radar-centric problem. For the communication-centric problem, we adopt quadratic transform to convexitify the multi-ratio fractional objective. Then, the rank-one constraint of communication beamforming vector is relaxed by semidefinite relaxation (SDR), and the tightness of SDR is further proved to guarantee the optimal waveform design with fixed clustering. For dynamic clustering, equivalent continuous functions are used to represent the non-continuous clustering variables. Successive convex approximation (SCA) is further utilized to convexitify the equivalent functions. Simulation results are provided to verify the effectiveness of all proposed designs