By John G. Webster (Editor)
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42. 43. 44. 45. 46. 47. 48. 49. 50. Target steering vector Adaptive weight vector Interference-plus-noise covariance matrix Number of adaptive degrees of freedom or antenna elements Number of radar pulses Doppler frequency Pulse repetition interval Pulse repetition frequency Coherent processing interval Signal-to-noise ratio Clutter-to-noise ratio Jammer-to-noise ratio Signal-to-interference-plus-noise ratio Probability of detection Probability of false alarm BIBLIOGRAPHY 1. R. Buderi The Invention that Changed the World, New York: Simon and Schuster, 1996.
These M adaptive ﬁlter outputs are then coherently combined using an M -pulse Doppler ﬁlter. Adaptation over sub-CPIs can mitigate interference that varies faster than the CPI length. Expressed using matrices, the adaptive weight vector for this STAP algorithm is Radar, Adaptive Figure 8. STAP radar signal-processing chain. Figure 9. STAP radar data cube. Figure 10. STAP algorithm taxonomy (12). Figure 11. SINR loss for the STAP algorithms considered. where 19 20 Radar, Adaptive Figure 12. Adaptive weight response for the STAP algorithms considered.
The conditional density of the AMF test is given by the noncentral F distribution where f (1 + α| ) is the GLRT’s conditional density given in Eq. (182). The AMF’s probability of detection may be obtained numerically by integration methods (44) or by moment methods (43). The AMF’s probability of false alarm, however, is given by the closed-form expression where is the Gauss hypergeometric function and Pochammer’s symbol (a)k is deﬁned in Eq. (175). The AMF test is seen in Fig. 12 to slightly outperform the GLRT for high SNRs.
55.Signal Processing by John G. Webster (Editor)