High-resolution digital beamforming of UWB signals based on Carathéodory representation for delay compensation and array extrapolation

To realize high-resolution digital beamforming(DBF)of ultra-wideband(UWB) signals, we propose a DBF method based on Carath ′eodory representation for delay compensation and array extrapolation. Delay compensation by Carath ′eodory representation could achieve high interpolation accuracy while using the single channel sampling technique. Array extrapolation by Carath ′eodory representation reformulates and extends each snapshot, consequently extends the aperture of the original uniform linear array(ULA) by several times and provides a better realtime performance than the existing aperture extrapolation utilizing vector extrapolation based on the two dimensional autoregressive(2-D AR) model. The UWB linear frequency modulated(LFM) signal is used for simulation analysis. Simulation results demonstrate that the proposed method is featured by a much higher spatial resolution than traditional DBF methods and lower sidelobes than using Lagrange fractional filters.

THE HIGH RESOLUTION MIMO RADAR SYSTEM BASED ON MINIMIZING THE STATISTICAL COHERENCE OF COMPRESSED SENSING MATRIX

Compressed Sensing (CS) theory is a great breakthrough of the traditional Nyquist sampling theory. It can accomplish compressive sampling and signal recovery based on the sparsity of interested signal, the randomness of measurement matrix and nonlinear optimization method of signal recovery. Firstly, the CS principle is reviewed. Then the ambiguity function of Multiple-Input Multiple-Output (MIMO) radar is deduced. After that, combined with CS theory, the ambiguity function of MIMO radar is analyzed and simulated in detail. At last, the resolutions of coherent and non-coherent MIMO radars on the CS theory are discussed. Simulation results show that the coherent MIMO radar has better resolution performance than the non-coherent. But the coherent ambiguity function has higher side lobes, which caused a deterioration in radar target detection performances. The stochastic embattling method of sparse array based on minimizing the statistical coherence of sensing matrix is proposed. And simulation results show that it could effectively suppress side lobes of the ambiguity function and improve the capability of weak target detection.