WRFRFT-based Coherent Detection and Parameter Estimation of Radar Moving Target With Unknown Entry/Departure Time

A moving target may enter a radar coverage area unannounced and leave after an unspecified period, which implies that the target's entry time and departure time are unknown. In the absence of these time information, target detection and parameter estimation (DAPE) will be severely impacted. In this paper, we consider the coherent detection and parameters estimation problem for a radar moving target with unknown entry time and departure time (that is, the time when the target appears-in/leaves the radar detection field is unknown), involving across range cell (ARC) and Doppler spread (DS) effects within the observation period. A new algorithm, known as window Radon Fractional Fourier transform (WRFRFT) is proposed to detect and estimate the target's time parameters (i.e., entry time and departure time) and motion parameters (i.e., range, velocity and acceleration). The observation values of a maneuvering target are first intercepted and extracted by the window function and searching along the motion trajectory. Then these values are fractional Fourier transformed and well accumulated in the WRFRFT domain, where the DAPE of target could be accomplished thereafter. Experiments with simulated and real radar data sets prove its effectiveness.Comment: 30 pages, 10 figure

Coherent Integration for Targets with Constant Cartesian Velocities Based on Accurate Range Model

Long-time coherent integration (LTCI) is one of the most important techniques to improve radar detection performance of weak targets. However, for the targets moving with constant Cartesian velocities (CCV), the existing LTCI methods based on polynomial motion models suffer from limited integration time and coverage of target speed due to model mismatch. Here, a novel generalized Radon Fourier transform method for CCV targets is presented, based on the accurate range evolving model, which is a square root of a polynomial with terms up to the second order with target speed as the factor. The accurate model instead of approximate polynomial models used in the proposed method enables effective energy integration on characteristic invariant with feasible computational complexity. The target samplings are collected and the phase fluctuation among pulses is compensated according to the accurate range model. The high order range migration and complex Doppler frequency migration caused by the highly nonlinear signal are eliminated simultaneously. Integration results demonstrate that the proposed method can not only achieve effective coherent integration of CCV targets regardless of target speed and coherent processing interval, but also provide additional observation and resolution in speed domain