This paper proposes an image-based automatic target detection algorithm to be used in clutter and sparse target
environments. We intend to apply the algorithm to an ultra-wideband multispectral radar concept by means of
employing multi-carrier waveforms based upon Orthogonal Frequency Division Multiplexing (OFDM) modulation.
Individual sub-bands of an OFDM waveform can be processed separately to yield range and cross-range reconstruction
of a target scene containing both targets and clutter. Target detection in resulting images will be performed and
contrasted with the detection performance of a traditional fixed-waveform Synthetic Aperture Radar system. The target
detection algorithm is implemented through the use of scalar and vector field operations performed on the images from
the reconstructed target scene. We hypothesize that the use of vector operations and field analysis will allow for an
adaptive approach to the detection of targets within clutter.
KEYWORDS: Radar, Signal to noise ratio, Transceivers, Imaging systems, Receivers, Telecommunications, Signal processing, Orthogonal frequency division multiplexing, Radar signal processing, Radar imaging
Orthogonal frequency division-multiplexing (OFDM) is rapidly emerging as a preferred method of UWB signaling in commercial applications aimed mainly at low-power, high data-rate communications. This paper explores the possibility of applying OFDM to use in imaging radar technology. Ultra-wideband nature of the signal provides for high resolution of the radar, whereas usage of multi-sub-carrier method of modulation allows for dynamic spectrum allocation. Robust multi-path performance of OFDM signals and heavy reliance of transceiver design on digital processors easily implemented in modern VLSI technology make a number of possible applications viable, e.g.: portable high-resolution indoor radar/movement monitoring system; through-the-wall/foliage synthetic aperture imaging radar with a capability of image transmission/broadcasting, etc. Our work is aimed to provide a proof-of-concept simulation scenario to explore numerous aspects of UWB-OFDM radar imaging through evaluating range and cross-range imaging performance of such a system with an eventual goal of software-defined radio (SDR) implementation. Stripmap SAR topology was chosen for modeling purposes. Range/cross-range profiles were obtained along with full 2-D images for multi-target in noise scenarios. Model set-up and results of UWB-OFDM radar imaging simulation study using Matlab/Simulink modeling are presented and discussed in this paper.
A coherent ultrawideband random noise radar system operating in the 1 - 2 GHz frequency range has been developed at the University of Nebraska. A unique signal processing procedure based upon heterodyne correlation techniques preserves phase coherence within the system, thereby enabling it to be used for synthetic aperture radar (SAR) imaging. The amplitude and the phase response of the system are used to form the frequency-domain target scattering profile matrix, which is then transformed into a SAR image. The ultrawideband nature of the transmit waveform presents some unique challenges in signal processing. A technique has been developed that achieves the theoretical cross-range resolution, and this method has been validated by field measurements at 200 meters range to target. Controlled close-range SAR experiments at 8 - 10 meters range clearly demonstrate the ability of the system to provide high resolution images of targets located in a cluttered background and to extract the spatial geometry of the scattering center locations. The paper will present theoretical basis for random noise SAR imaging as well as experimental results and discussion.
The University of Nebraska has developed an ultrawideband coherent random noise radar that accomplishes phase-coherent processing of the received data. The system operates over the 1 - 2 GHz frequency range, and achieves phase coherence using heterodyne correlation of the received signal with the time delayed replica of the transmitted signal. Knowledge of the phase of the received signal and its time dependence due to the motion of the target permits the system to be configured as a Doppler radar for detecting both linear and rotational motion. Preliminary simulation and experimental results presented last year indicate confidence in the system's ability to extract linear and rotation Doppler velocities of targets. The accuracy with which Doppler spectra of moving objects can be estimated is dependent not only upon the phase performance of various components within the radar system, but also upon the uncertainties arising from random and systematic internal and external factors. This-paper describes the simulation studies to characterize the uncertainties in Doppler measurement due internal and external mechanism.