A Modified Radon Fourier Transform for GNSS-Based Bistatic Radar Target Detection

Radar Maneuvering Target Detection Based on Scaling Processing and Radon-fourier Transform

A novel long-time coherent integration method, i.e., scaling processing and Radon-Fourier transform (SPRFT), is proposed to detect the low-observable manuevering target, which can compensate the range and Doppler migrations simultaneously. The target signal can be well accumulated as an obvious peak in the centroid frequency-chirp rate (CFCR) domain by simple FT calculations. It is shown that p...

3D Fourier based discrete Radon transform

The Radon transform is a fundamental tool in many areas. For example, in reconstruction of an image from its projections (CT scanning). Recently A. Averbuch et al. [SIAM J. Sci. Comput., submitted for publication] developed a coherent discrete definition of the 2D discrete Radon transform for 2D discrete images. The definition in [SIAM J. Sci. Comput., submitted for publication] is shown to be ...

Bistatic synthetic aperture radar using GNSS as transmitters of opportunity

Adaptive Based Multiobjective Optimization Based Node Placement and Target Detection in Bistatic Radar Network

A bistatic radar network that consists of multiple separated radar transmitters (TXs) and receivers (RXs), aiming to detect a target on a set of points of interest (PoIs) is considered. The detection range of a bistatic radar depends on both locations of the TX and RX. The design of the bistatic radar network is investigated by studying the problem of optimally placing a number of radar transmi...

General Linear Chirplet Transform and Radar Target Classification

In this paper, we design an attractivealgorithm aiming to classify moving targets includinghuman, animal, vehicle and drone, at groundsurveillance radar systems. The non-stationary reflectedsignal of the targets is represented with a novelmathematical framework based on behavior of thesignal components in reality. We further propose usingthe generalized linear chirp transform for the analysisst...