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Absfracf-Inverse synthetic a p e r t u r e radar (ISAR) images can be used for radar target classification. To achieve a suitable cross-range resolution in these ISAR images, a relative aspect change is required between t h e target and t h e radar. In many encounter scenarios this prerequisite aspect change is not available. In these cases a high resolution range profile (HRRP) must be used for target classification. This paper presents a coherent averaging algorithm which provides t h e best possible HRRP for a given radar dwell time. T h e resultant HRRP is thresholded with a CFAR technique. Coherent averaging is compared with non-coherent averaging and coherent averaging is found to provide HRRPs with a higher SNR.

With the increased availability of coherent wideband radars, there has been a renewed interest in radar target recognition. A large bandwidth gives high resolution in range which means target recognition may be possible. We examine some of the problems of classifying high resolution range profiles (HRRP), and investigate simple preprocessing techniques which may aid subsequent target classification. We apply these techniques to HRRP data acquired at a local airport using the Microwave Radar Division (MRD) mobile radar facility. We find that we can reliably distinguish between Boeing 727 and Boeing 737 aircraft over a range of aspect angles.

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