WRFRFT-based coherent detection and parameter estimation of radar moving target with unknown entry/departure time

Abstract

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 WR-FRFT domain, where the DAPE of target could be accomplished thereafter. Experiments with simulated and real radar data sets prove its effectiveness.

Radar High-Speed Target Detection Based on Improved Minimalized Windowed RFT

“…where  denotes the wavelength. The constant phase terms have been absorbed into 2 A [34][35][36]. During the illumination time, the high speed v induces the envelop offset in (5).…”

Subaperture Keystone Transform Matched Filtering Algorithm and Its Application for Air Moving Target Detection in an SBEWR System

“…To improve detection performance and get the utmost out of the phase information, coherent integration methods are widely developed , which can be further subdivided into four categories, i.e., Radon-based methods [15][16][17][18][19][20][21][22][23][24], Keystone transform (KT)-based methods [25][26][27][28][29], matched filtering (MF)-based methods [30][31][32], and reduced-order (RO)-based methods [33][34][35][36][37]. The core idea of the RFT and GRFT is that the range and Doppler phase variations are compensated simultaneously by searching all possible target motion states.…”

“…The core idea of the RFT and GRFT is that the range and Doppler phase variations are compensated simultaneously by searching all possible target motion states. Followed by this main idea, many novel kernel functions are widely developed, including linear transform such as Radon-fractional Fourier transform (RFRFT) [17], and nonlinear transform such as Radon-Lv's distribution (RLVD) [18], and others kernel function tools in [19][20][21][22][23][24]. In spite of the coherent integration gain can be obtained in these methods, the ergodic search operation in Radon-based methods will inevitably introduce unbearable computational burden.…”

“…3) Compared with nonlinear kernel function-based methods in [18][19][20][21][22][23][24] and [33][34][35][36][37], the proposed method is immune to performance loss induced by nonlinear operation, resulting in applicable in low SNR environment.…”

Heuristic Path Planning Method for Multistatic UAV-Borne SAR Imaging System

“…Compared with airborne and spaceborne SAR, UAV-borne SAR has a shorter radar range and narrower beam coverage [9,30], it often works in spotlight SAR mode. Higher imaging resolution can be obtained by the accumulation of echo data through long-time observation of the region of interest [29,[31][32][33]. For MuUAV-SAR imaging system, high imaging resolution is highly dependent on a good path, and it is also very important to comprehensively consider the path distance of multiple platforms, terrain threats and other factors.…”