Image enhancement in forward imaging radar using modified apodisation technique

Abstract

Forward imaging radar using an UWB signal has been developed by many researchers. The image quality in this radar is not satisfactory because of the limitation of aperture length. Proposed is an image enhancement method using a modified apodisation technique in forward imaging radar. An experiment is carried out to validate the proposed method. The azimuth resolution and peak-to-sidelobe ratio are improved by the proposed method by up to about 11.7% and 10 dB, respectively.

Cross‐range resolution improvement in forward‐looking imaging radar using autoregressive model‐based data extrapolation

“…To reduce the sidelobe level in the FIRA system, the sidelobe apodisation methods such as the recursive sidelobe minimisation technique, the spatially variant apodisation (SVA) technique and modified SVA [5, 14] have been published by other researchers. Fig.…”

“…In this paper, images are formed by a back‐projection (BP) method in the time domain [5, 9]. It is also possible to apply other image‐formation techniques such as range‐Doppler method, chirp‐scaling and Omega‐K algorithms [10].…”

“…The range resolution of a radar image is directly related to the bandwidth of the transmitting signal, and the cross‐range resolution is determined by the effective length of the antenna aperture [2]. In real aperture array imaging systems used for forward‐looking imaging applications [3–5], the target information can be sampled in a parallel manner by a real aperture antenna array during single‐snapshot illumination. However, the cross‐range resolution is severely limited by short length of the physical array.…”

Omega-K Algorithm Using Plane Wave Approximation for Forward-Looking Imaging Radar

“…Most previous research on FIRA has adopted the backprojection (BP) algorithm for image formation [3,4]. However, the BP algorithm requires additional processing steps to reduce the sidelobes of FIRA images [6] and to increase spatial resolution. In addition, computation time depends on the size of the interested region due to the process that computes pixel-based received signals in the time domain.…”