442 research outputs found
A Novel STAP Algorithm for Airborne MIMO Radar Based on Temporally Correlated Multiple Sparse Bayesian Learning
In a heterogeneous environment, to efficiently suppress clutter with only one snapshot, a novel STAP algorithm for multiple-input multiple-output (MIMO) radar based on sparse representation, referred to as MIMOSR-STAP in this paper, is presented. By exploiting the waveform diversity of MIMO radar, each snapshot at the tested range cell can be transformed into multisnapshots for the phased array radar, which can estimate the high-resolution space-time spectrum by using multiple measurement vectors (MMV) technique. The proposed approach is effective in estimating the spectrum by utilizing Temporally Correlated Multiple Sparse Bayesian Learning (TMSBL). In the sequel, the clutter covariance matrix (CCM) and the corresponding adaptive weight vector can be efficiently obtained. MIMOSR-STAP enjoys high accuracy and robustness so that it can achieve better performance of output signal-to-clutter-plus-noise ratio (SCNR) and minimum detectable velocity (MDV) than the single measurement vector sparse representation methods in the literature. Thus, MIMOSR-STAP can deal with badly inhomogeneous clutter scenario more effectively, especially suitable for insufficient independent and identically distributed (IID) samples environment
Non-Linear Signal Processing methods for UAV detections from a Multi-function X-band Radar
This article develops the applicability of non-linear processing techniques
such as Compressed Sensing (CS), Principal Component Analysis (PCA), Iterative
Adaptive Approach (IAA) and Multiple-input-multiple-output (MIMO) for the
purpose of enhanced UAV detections using portable radar systems. The combined
scheme has many advantages and the potential for better detection and
classification accuracy. Some of the benefits are discussed here with a phased
array platform in mind, the novel portable phased array Radar (PWR) by Agile RF
Systems (ARS), which offers quadrant outputs. CS and IAA both show promising
results when applied to micro-Doppler processing of radar returns owing to the
sparse nature of the target Doppler frequencies. This shows promise in reducing
the dwell time and increase the rate at which a volume can be interrogated.
Real-time processing of target information with iterative and non-linear
solutions is possible now with the advent of GPU-based graphics processing
hardware. Simulations show promising results
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