Non-linear prediction of inverse covariance matrix for STAP
2007 IEEE International Conference on Acoustics, Speech and Signal …, 2007•ieeexplore.ieee.org
For bistatic ground moving target indication radar, the clutter Doppler frequency depends on
range for all array geometries. This range dependency leads to problems in clutter
suppression through STAP techniques. In this paper, we propose a new approach of
applying non-linear prediction theory to address the range dependency problem in bistatic
airborne radar systems. This technique uses a non-linear function to obtain an estimate of
the range-dependent inverse covariance matrix. Simulation results suggest a non-linear fit …
range for all array geometries. This range dependency leads to problems in clutter
suppression through STAP techniques. In this paper, we propose a new approach of
applying non-linear prediction theory to address the range dependency problem in bistatic
airborne radar systems. This technique uses a non-linear function to obtain an estimate of
the range-dependent inverse covariance matrix. Simulation results suggest a non-linear fit …
For bistatic ground moving target indication radar, the clutter Doppler frequency depends on range for all array geometries. This range dependency leads to problems in clutter suppression through STAP techniques. In this paper, we propose a new approach of applying non-linear prediction theory to address the range dependency problem in bistatic airborne radar systems. This technique uses a non-linear function to obtain an estimate of the range-dependent inverse covariance matrix. Simulation results suggest a non-linear fit for the model (nonlinear relationship between the inverse covariance matrices) and show an improvement in processor performance as compared to conventional STAP methods.
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