For the integration detection of near space hypersonic weak targets by high pulse repetition frequency (PRF) radar, a novel method named Multi-Hypothesis Fuzzy-Matching Radon transform (MHFM-RT) is proposed for the near space hypersonic target detection and tracking. For remote hypersonic target detection, to avoid range ambiguity, current radars always use a low PRF mode, which limit the number of pulse accumulations. Using the high PRF mode, the fuzzy folding will appear in the target range measurements when target trajectory crosses range fuzzy intervals. Therefore, there is a contradiction between range ambiguity and energy accumulation. The proposed method is used to match the fuzzy measurements, so as to realise the correct integration in the condition of range ambiguity. Firstly, considering the need of range ambiguity resolution, the mode of staggered PRF is used. Secondly, the first frame measurements are periodically extended for multiple-fuzzy hypothesis. Finally, the weak target track is accumulated in MHFM-RT domain, and the signal integration and ambiguity resolution can be realised simultaneously. The proposed method expands the Variable-Diameter-Arc-Helix Radon transform (VDAH-RT) method to fuzzy folding conditions. Compared with the existing methods, for 7-scan measurements non-coherent integration, the detection sensitivity of the proposed method is about 0.5–1 dB higher than that of the IMM hybrid filter algorithm, and about 1 dB higher than that of the RHT-TBD approach, and it needs less storage space and has higher detection probability.

中文翻译：

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基于多假设模糊匹配氡变换的高脉冲重复频率雷达检测高超声速弱目标

针对高脉冲重复频率(PRF)雷达对临近空间高超声速弱目标的集成检测，提出了一种临近空间高超声速目标检测与跟踪的多假设模糊匹配氡变换(MHFM-RT)新方法。对于远程高超声速目标检测，为了避免距离模糊，当前的雷达总是使用低PRF模式，这限制了脉冲累积的数量。使用高PRF模式，当目标轨迹穿过距离模糊区间时，目标距离测量中将出现模糊折叠。因此，范围模糊与能量积累之间存在矛盾。该方法用于对模糊测量进行匹配，从而实现距离模糊情况下的正确积分。首先，考虑到距离模糊度分辨率的需要，采用交错PRF模式。其次，针对多重模糊假设定期扩展第一帧测量。最后，在MHFM-RT域中累积弱目标航迹，同时实现信号积分和模糊度消解。该方法将变直径弧螺旋氡变换（VDAH-RT）方法扩展到模糊折叠条件。与现有方法相比，对于7扫描测量非相干积分，该方法的检测灵敏度比IMM混合滤波算法高约0.5~1 dB，比RHT-1高约1 dB。 TBD方法，需要更少的存储空间并且具有更高的检测概率。