Herein, a robust constant false alarm rate (CFAR) detector with ordered statistic of subreference cells (OSS-CFAR) is proposed in multiple target situations. This detector can improve background level estimation and reduce computational complexity using sub-reference cells. The detection performance of the OSS-CFAR detector and of conventional CFAR detectors in multiple target situations are investigated and compared using computer simulations and experimental data with sea clutter. The simulations and experimental results show that the OSS-CFAR detector achieves robust detection performance with low computational complexity, whereas conventional CFAR detectors suffer performance degradation in multiple target situations. At the clutter edge, the OSS-CFAR detector with appropriate parameters achieves an acceptable false alarm rate compared to conventional CFAR detectors.INDEX TERMS Constant false alarm rate detector, clutter edge, multiple target situations, ordered statistic of sub-reference cells.
Airborne radars should track an enemy aircraft from maximum to minimum range very accurately to assist in immediate action. Meanwhile, when the target aircraft enters into very close range, such as a few kilometers, the effect of the glint on the angle measurement error increases. In this study, the design of signal processing and waveform consideration of short-range tracking mode of airborne radars is described. The proposed mode design includes the coherence limitation of the CPI and usage of multiple bursts to reduce the glint effect. The proposed method is verified via flight tests, and it is confirmed that the signal processing works accurately with a reduced angle measurement error.
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