Omar A. Yeste-Ojeda

Atomic decomposition for radar applications

In this paper, we explore the promising capabilities of atomic decomposition (AD) for radar-related applications from a practical point of view. Some enhancements and new approaches are proposed herein, and their implementations are fully detailed. We apply the AD algorithms in two different environments, for signal detection where high sensitivity is the main requirement, and for inverse synthetic aperture radar (ISAR) imaging where focused images, target feature extraction, and computational burden are the fundamental concerns.

Low-Cost CW-LFM Radar Sensor at 100 GHz

This paper presents a W -band high-resolution radar sensor for short-range applications. Low-cost technologies have been properly selected in order to implement a versatile and easily scalable radar system. A large operational bandwidth of 9 GHz, required for obtaining high-range resolution, is attained by means of a frequency multiplication-based architecture. The system characterization to identify the performance-limiting stages and the subsequent design optimization are presented. The assessment of system performance for several representative applications has been carried out.

Facet Model of Moving Targets for ISAR Imaging and Radar Back-Scattering Simulation

A facet model of targets is proposed to simulate inverse synthetic aperture radar (ISAR) images and radar back-scattering of moving targets with rigid and nonrigid motions. Targets are composed of solid objects which are modeled by triangular facets. It is shown that a facet can be treated as an equivalent point-scatterer whose radar cross section (RCS) and position depend on the shape of the triangle, the frequency, and the angle of incidence. A shadowing algorithm is also developed to detect the facets which actually have influence on the signal received by the radar. Besides, a facet division algorithm is implemented to improve the result of the shadowing algorithm and to have at least one facet per resolution cell. Finally, we apply our simulator to obtain the ISAR images of a ship and a helicopter and to calculate the micro-Doppler signature of a human.

Cyclostationarity-based signal separation in interceptors based on a single sensor

This work explores the capabilities of cyclostationarity for interference rejection when only one sensor is available. The aim is to detect an unknown signal when it overlaps simultaneously in time and frequency with an interference whose cyclic spectrum is known. The approach is to split separation and detection problems: Firstly, the interference is separated by means of a blind adaptive frequency shift (FRESH) filter. Then, detection is made on the residual, which is assumed to consist of noise and the signal of interest. Simulation results prove a sensitivity improvement in practical situations.

Experimental radar imager with sub-cm range resolution at 300 GHz

This paper presents a high range resolution radar sensor working in the submillimeter-wave band for standoff detection and security applications. Low-cost technologies have been properly selected in order to implement a versatile and easily scalable radar system. A large operational bandwidth, required for high range resolution, is attained by means of a frequency multiplication-based architecture. This radar system sweeps a bandwidth of 27 GHz. The final application allows the generation of 3D images by means of the radar front-end integrated with a bifocal ellipsoidal Gregorian reflector system. The scene of interest is elliptically scanned at a standoff range of 8 m.

Limitations of Spectral Correlation Based Detectors

This work explores the capabilities of spectral correlation based detectors for partially or completely unknown signals corrupted by Gaussian noise. The main contribution is twofold: Firstly, the cyclostationary model is shown to be less suitable for detection purposes than the stationary model. Secondly, analytic approximations are derived for the detection and false alarm probabilities, under the assumption of long observation time.

Integrated direct RF sampling front-end for VHF avionics systems

For a market sector where size, weight, power and cost (SWaP-C) optimization is crucial, specifically with the proliferation of unmanned aerial systems, this paper proposes the minimization of SWaP-C requirements through a Direct RF Sampling (DRFS) approach. This work focuses on the integration of avionics systems operating at the VHF band, i.e. VOR, ILS (LOC and GS) and aeronautical communications (voice, ACARS, VDL, etc.). The scope of this work is to present a feasibility study of the proposed integrated avionics. Several factors must be taken into account: First, the selection of a best sampling frequency is a key point in the design of the system. Two approaches to sampling frequency selection are considered: 1) static, whose aim is to digitize and lock the frequency bands fully; and 2) dynamic, where only the occupied channels are sampled without aliasing. The second important factor to be considered in addition to sampling frequency refers to the maximum dynamic range of the system. The dynamic range of the Analog to Digital Converter (ADC) has to be large enough to receive without distortion the most and the least powerful signals at the antenna. Finally, this work studies the digital down-converter (DDC) architecture to be hardware implemented in a Field Programmable Gate Array (FPGA), and quantitatively analyzes the resources required for its implementation.

Multi-linear subspace estimation and projection for efficient RFI excision in SIMO systems

The paper introduces the multi-linear algebra framework to the radio frequency interference (RFI) excision research by proposing a multi-linear subspace estimation and projection (MLSEP) algorithm for efficient RFI excision in single-input multiple-output (SIMO) systems. Thereafter, the paper compares the MLSEP algorithm with the state-of-the-art projection-based RFI excision algorithms. Eventually, Matlab® Monte-Carlo simulations corroborate that MLSEP outperforms the state-of-the-art projection-based RFI excision algorithms.

Analysis of ISAR images of a helicopter by a facet model

A triangular facet model of targets is proposed to generate ISAR images. Targets are composed of solid objects which are modeled by triangular facets. It is shown that the facets have an equivalent point-scatterer whose radar cross section and position depend on the shape of the triangle, the frequency and the angle of incidence. It is developed a shadowing algorithm to detect the facets which actually have influence on the signal received by the radar. This model is applied to study the ISAR images of a helicopter with two different transmitted signals, a rectangular pulse waveform and a linear frequency modulated waveform to identify the main features of the ISAR images for future classification purposes.

CFAR detection of chirplets in coloured Gaussian noise

Two detectors based on the GLRT (generalized maximum likelihood ratio test) are presented to detect a chirplet in coloured Gaussian noise for known and unknown covariance structures, respectively. They are applied to detect multiple chirplets by atomic decomposition, which is modified to account for the operating conditions of both detectors. Both detectors are CFAR with respect to the noise power. The second one is CFAR with respect to the covariance structure as well.