Inspired by recent advances in multiple-input multiple-output (MIMO) communications, this proposal introduces the statistical MIMO radar concept. To our knowledge, this is the first time that the statistical MIMO is being proposed for radar. The fundamental difference between statistical MIMO and other radar array systems is that the latter seek to maximize the coherent processing gain, while s...

The paper draws attention to the emerging military capabilities of laser radar by describing state-oftechnology sensor processing results for applications involving helicopter obstacle warning, automatic target identification at far range and automatic target detection and classification at close range. In all applications sensor processing requires accurate motion compensation using navigation...

Radar images are affected by a multiplicative noise depending on the underlying signal (the ground reflectivity) due to the coherence of the radar wavelength. Images present a strong pixel to pixel variability considerably reducing the efficiency of target detection and classification algorithms. We propose in this study filtering this noise using image multiresolution analysis. The value of th...

Radar engineers and operators measure the radar return of a given target from a given angle in terms of its Radar Cross Section (RCS), from which they can detect and completely identify that target as its type, direction, and speed. The RCS of a target may have a huge value from one angle and at the same time has a very small value from another angle. So the challenge is to reduce the RCS of an...

This paper presents a radar target recognition method using kernel locally linear embedding (KLLE) and a kernel-based nonlinear representative and discriminative (KNRD) classifier. Locally linear embedding (LLE) is one of the representative manifold learning algorithms for dimensionality reduction. In this paper, LLE is extended by using kernel technique, which gives rises to the KLLE algorithm...

Forward scatter radar (FSR), as a specially configured bistatic radar, is provided with the capabilities of target recognition and classification by the Shadow Inverse Synthetic Aperture Radar (SISAR) imaging technology. This paper mainly discusses the reconstruction of radio holographic signal (RHS), which is an important procedure in the signal processing of FSR SISAR imaging. Based on the an...

In this paper our recent investigation and experimental results of the polarimetric SAR classification of the data for the Glen Affric radar project is presented. The polarimetric classification is one of the most important applications of the radar polarimetry in remote sensing. The unsupervised and supervised polarimetric classification of the Glen Affric data in respect to the classified Ari...

Automatic target recognition (ATR) of synthetic aperture radar (SAR) image is investigated. One feature extraction algorithm of SAR image based on multilayer auto-encoder is proposed. The method makes use of a probabilistic neural network, restricted Boltzmann machine (RBM), modeling probability distribution of environment. Through the formation of more expressive multilayer neural network, the...

This research presents an ambiguity function analysis of the digital audio broadcast (DAB) waveform and one signal detection approach based on signal space projection techniques that effectively filters the direct-path signal from the receiver target channel. Currently, most Passive Coherent Location (PCL) research efforts are focused and based on frequency modulated (FM) radio broadcasts and a...