Abstract:
This letter presents a novel method used to find the constant false alarm rate (CFAR) threshold after coherently compressing one or more dimensions of the radar image, ge...Show MoreMetadata
Abstract:
This letter presents a novel method used to find the constant false alarm rate (CFAR) threshold after coherently compressing one or more dimensions of the radar image, generally the ones obtained from a phased array or multiple input multiple output (MIMO) diversity. The method provides a significantly large improvement in the numerical complexity of the processing chain at the cost of a slightly lower probability of detection for a fixed probability of false alarm. The method is particularly useful for real-time applications such as assisted and autonomous driving, where CFAR is applied to the range-Doppler map to generate a point cloud before angular estimation is done. The method may also be extended for Earth observation (EO) or surveillance applications where real-time processing is required. The proposed method is intended as a pre-processing step to the CFAR detection and is compatible with any CFAR algorithm that assumes Gaussian noise. The method implies finding a CFAR threshold calculated from a low-SNR non-coherent integrated radar signal and analytically mapping it to the high-SNR coherent integrated radar signal for improved detection. The proposed method is first presented theoretically and then evaluated in both simulated and experimental environments.
Published in: IEEE Geoscience and Remote Sensing Letters ( Volume: 20)