This paper presents a novel deconvolution algorithm designed to estimate the impulse response of buried objects based on ground penetrating radar (GPR) signals. The impulse response is a rich source of information about the buried object and therefore very useful for intelligent signal processing of GPR data. For example, it can be used in a target classification scheme to reduce the false alar...

The target recognition from Radar images was a crucial step in our research. This paper presents a process and an adopted approach for Automatic Target recognition using Inverse Synthetic Aperture Radar (ISAR) image. Indeed, the process adopted is composed of three steps. In the first step, we achieve the edge detection using of three techniques: Fisher, Kmeans and Expectation-Maximization (E-M...

The effect of target micro-motions on the Synthetic Aperture Radar signal results in micro-Doppler target signatures. These micro-Doppler signatures can be a useful source of information for target classification. However the presence of stationary target and noise in the scene makes the extraction of the micro-Doppler signature a difficult challenge. In this paper a micro-Doppler signature ext...

A new method to recognize ship target in SAR imagery using an Active Appearance Model (AAM) is proposed in this paper. The AAM can describe both shape and grey-level appearance of target which can present the SAR target more accurately.The application of AAM in SAR targets recognition was discussed in details. And the effectiveness of the method was demonstrated through the ship target classifi...

Nowadays, Radar systems have many applications and radar imaging is one of the most important of these applications. Inverse Synthetic Aperture Radar (ISAR) is used to form an image from moving targets. Conventional methods use Fourier transform to retrieve Doppler information. However, because of maneuvering of the target, the Doppler spectrum becomes time-varying and the image is blurred. Joi...

This paper investigates the use of micro-Doppler spectrogram signatures flying targets, such as drones and birds, to aid in their remote classification. Using a custom-designed 10-GHz continuous wave (CW) radar system, measurements from different scenarios on variety targets were recorded create datasets for image Time/velocity spectrograms generated analysis multiple birds used target identifi...

The multifractal characteristics of return signals from aircraft targets in conventional radars offer a fine description of dynamic characteristics which induce the targets’ echo structure; therefore they can provide a new way for aircraft target classification and recognition with low-resolution surveillance radars. On basis of introducing the mathematical model of return signals from aircraft...

In this paper, we propose a two-stage multi-task learning representation method for the classification of synthetic aperture radar (SAR) target images. The first stage of the proposed approach uses multi-features joint sparse representation learning, modeled as a ℓ 2 , 1 -norm regularized multi-task sparse learning problem, to find an effective subset of training samples. Then, a new dictionary...

A bistatic High Frequency (HF, or 3-30 megahertz band) radar has been developed for dual-use application to ocean current mapping and ship vector tracking. The radar can be deployed in a multi-frequency version, allowing it to sample ocean currents at different depths between 20 centimeters and 3 meters, and thus map ocean current vertical shear. The multi-frequency feature allows for more robu...

Multi-transmitter multi-receiver passive radar, which locates target in the surveillance area by the reflected signals of the available opportunistic transmitter from the target, is of interest in many applications. In this paper, we investigate different signal processing scenarios in multi-transmitter multi-receiver passive radar. These scenarios include decentralized processing of reference ...