LINEAR PREDICTION APPROACH IN AIRBORNE ADAPTIVE ARRAYS

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LINEAR PREDICTION APPROACH IN AIRBORNE ADAPTIVE ARRAYS

To cope with the time-varying and Dopper-broadened clutter in airborne phase array radars, it is required that the signal processing should be adaptive and two-dimensional both in time and in space. However, the optimum two-dimensional adaptive processing is hard to realize real-timely because it requires a large amount of computation. From the idea of approximating the clutter process by using an auto regressive process, a linear prediction approach is proposed to realize the adaptive space-time processing of airborne adaptive array signals. The research shows that the clutter process can be well approximated by a low-order AR process, so a low-order linear prediction receiver can get a sub-optimum performance at a very low expense. Besides, the low-order linear prediction receiver has additional degrees of freedom to cope with other colored noises and interferences. In consideration of the many advantages of the linear prediction receiver in both algorithms and realizations, it has a good prospect in its application to air borne adaptive array signal processing.