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Study of model-order selection algorithms and their applicability to adaptive clutter suppression

机译:模型阶选择算法及其在自适应杂波抑制中的应用研究

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The problem of predicting the optimum autoregressive (AR) model order is addressed in the context of adaptive radar clutter suppression. The applicability of existing model-order selection criteria to AR clutter models was studied through a computer simulation of a scanning Doppler radar. Reasonably good predictions were achieved with the Akaike final-prediction-error criterion and the Parzen criterion-autoregressive-transfer when the coefficients obtained in one scan of the radar antenna were used on the data obtained in the next scan.
机译:在自适应雷达杂波抑制的背景下解决了预测最佳自回归(AR)模型顺序的问题。通过扫描多普勒雷达的计算机仿真研究了现有模型顺序选择标准对AR杂波模型的适用性。当将在雷达天线的一次扫描中获得的系数用于下一次扫描中获得的数据时,使用赤池最终预测误差准则和Parzen准则-自回归传递可以实现合理的良好预测。

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