Classification of scaled radar target data collected at ultrasound frequencies

Target recognition and classification applied to radar and sonar systems has become of great importance in recent years following the development of high range resolution systems that allow a much more detailed target sensing. Although a lot of research has been done on these topics, classification of targets under all weather and clutter condition remains a key problem in many military applications and often not much data is available. Ultrasound measurements offer a relatively simple and inexpensive way to collect target data that can be used to exploit the performance of classifiers on scaled targets. In this thesis, classification of scaled radar target data collected at ultrasound frequencies is presented. Performance of various classifiers is assessed as a function of parameters, such as target features, SNR and angular perspectives

Implementation of tracking algorithms for multistatic systems

Due to the increased prevalence of ubiquitous communication technologies and the reduced cost of electronic components, there is an increasing interest in developing networked radar systems. Such networked radar systems offer potential benefits in robustness as well as improvements in performance for detection, tracking and classification. As a branch of applied computer sciences sensor data fusion addresses the ability to process this vast quantity of information, generated by multiple sources, in an effective way. The purpose of this thesis is to validate the tracking algorithms implemented, to determine whether they are capable of identifying and tracking two closely spaced targets, to determine the capability of the system to track a target that moves with fast maneuvers as well as the ability to handle a potential simultaneous attack from both the air and the sea. We present a method for multiple target tracking using multiple sensors both for passive and active sensors. Firstly, regarding active radar, we describe an algorithm for combining range-Doppler data from multiple sensors to perform multi-target tracking. In particular we considered the problem of very poor azimuth resolution. In this case more than two sensors are needed to triangulate target tracks and techniques like multilateration are needed to overcome the problem. Then two tracking algorithms for bistatic DVB-T passive radar based on the Extended Kalman Filter (for single target tracking) and on the Kalman filter (for multiple target tracking), exploiting measurement of bistatic range and bistatic velocity of a target are described. Also the direction of arrival of the target is estimated through beamforming and then used in the tracking model. The algorithms have been tested and validated by using real data

Passive multifrequency forward-scatter radar measurements of airborne targets using broadcasting signals

This paper demonstrates the feasibility and effectiveness of forward-scatter radar (FSR) target detection based on the signals of opportunity made available by standard radio and TV broadcast transmission stations. This passive FSR (P-FSR) operation is obtained by means of a simple and robust correlation process based on self-mixing. This is shown to be very effective in extracting the characteristic FSR modulation produced by airborne targets, from the signals received from frequency modulated, digital audio broadcasting, and digital video broadcasting transmitters of opportunity. Target detectability is discussed as a function of the carrier frequency, the target size, and its height at the baseline crossing. Experimental results are shown using a wide variety of sources of opportunity, target types, baselines, and receiver configurations. The target signatures obtained from the different illuminators are compared and ways of extracting the kinematic parameters of the aircraft are discussed. This validates the claimed effectiveness and robustness of the P-FSR with the presented processing scheme

Multi-sensor multi-target tracking based on range-Doppler measurement

In this paper, we present a method for multiple target two-dimensional tracking using multiple sensors with very low azimuth resolution. Due to the scarce azimuth resolution, the data association is performed using range and Doppler information only from four radars. The proposed algorithm is tailored to perform in maritime scenarios. In order to test the algorithm performance, sea clutter data have been taken under consideration when simulating data.</p

Multi-sensor multi-target tracking based on range-Doppler measurement

In this paper, we present a method for multiple target two-dimensional tracking using multiple sensors with very low azimuth resolution. Due to the scarce azimuth resolution, the data association is performed using range and Doppler information only from four radars. The proposed algorithm is tailored to perform in maritime scenarios. In order to test the algorithm perform- ance, sea clutter data have been taken under consideration when simulating data

Multi-sensor multi-target tracking based on range-Doppler measurement

In this paper, we present a method for multiple target two-dimensional tracking using multiple sensors with very low azimuth resolution. Due to the scarce azimuth resolution, the data association is performed using range and Doppler information only from four radars. The proposed algorithm is tailored to perform in maritime scenarios. In order to test the algorithm performance, sea clutter data have been taken under consideration when simulating data.</p