Abstract

Signal processor design for detection and tracking of high speed manoeuvring targets is still a challenging problem in radar literature. To effectively process and extract actionable information from this class of targets, high pulse repetition frequency (HPRF) radars are employed. HPRF radars transmit a large number of pulses in short duration of time to swiftly gather information about the target of interest. Because of this high sampling rate, HPRF radars provide accurate relative velocity (V <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</inf> ) information but have ambiguity in range estimations. However, to unfold the target trajectory using only V <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</inf> information requires additional data about the initial conditions of the target and velocity of the transmitter. The HPRF processing is further complicated if there are multiple manoeuvring (accelerating or decelerating) targets in scene. The reflections from this class of targets are spread out in both time and frequency rendering classical signal processing techniques futile. In this work we propose a multichannel radar signal processor (RSP) design to address the afore mentioned limitations. The proposed RSP consists of two parallel channels designed to address the problems of range ambiguity, doppler extraction and doppler association. We demonstrate the effectiveness of the proposed approach using several challenging use cases. We propose fusion of compressed sensing (CS), doppler filter bank (DFB) and fractional Fourier transform (FrFT) operating in a parallel channel architecture to achieve the objective. All the channels are designed to work synchronously complementing each other for an effective and robust RSP design.

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