Domenico Vigilante

Comparison of recursive and batch processing for impact point prediction of ballistic targets

The paper deals with the problem of impact point prediction of ballistic targets (BT) by processing measurements acquired either by 3D surveillance or multifunctional phased-array radars. It is assumed that the radar acquires a limited number of measurements that do not encompass the whole target trajectory; thus the established target track has to be extrapolated ahead in time in order to predict the coordinates of the impact point. In this paper we compare performance of batch (i.e. maximum likelihood estimation, MLE) and recursive (extended Kalman filter EKF and unscented Kalman filter UKF) filtering techniques.

A Real Time Test Bed for 2D and 3D Multi-Radar Tracking and Data Fusion with Application to Border Control

This paper describes part of the activities required to model and assess the performance of a national integrated system (NIS) in the context of homeland security and in particular on border control issues. The border control requires an accurate surveillance of the terrestrial, maritime and overland boundaries, thus involving a wide number of heterogeneous sensors, command and control centres, platforms and communication networks. One of the layers of the integrated system is composed by radar sensors; these sensors can be ground or ship based, 1D or 3D. The paper deals with the problem of correlation and fusion of track data pertaining to ground and ship based, 2D and 3D radar sensors directly in the radar sites. Then, the improved (i.e. more accurate) information can be soon made available for a number of radar functions, such as: (i) re-pointing of the beam along the threat direction of arrival, (ii) energy and time management, (iii) cue of other sensors (i.e. infrared) or proper reaction means (patrol boat), (iv) preliminary classification of potential hostile targets. The updating and testing of the data extractor (DE) of a notional surveillance radar system is presented; the modified hardware and software is capable of acquiring, managing and fusing tracks pertaining to the radar system housing the DE and to other systems connected to the DE itself

Classification and launch-impact point prediction of ballistic target via multiple model maximum likelihood estimator (MM-MLE)

The paper deals with the problems of (i) launch and impact point prediction (LPP, IPP) of ballistic targets (BT) and (ii) BT classification by processing measurements acquired either by 3D surveillance or multifunctional phased-array radars. It is assumed that the radar acquires a limited number of measurements (plots) that do not encompass the whole target trajectory; thus, the established target track has to be extrapolated ahead in time in order to predict the coordinates of the impact point. A procedure based on multiple model maximum likelihood estimator (MM-MLE) has been conceived and tested using a Monte Carlo simulation approach; the parameters selected for testing are the probability of BT correct classification (Pcc), the IPP and the LPP. The new procedure is compared with the estimator described in A. Farina et al. (2004).

New approach to 2d Medium PRF ambiguity resolution with application to air surveillance radar

This paper illustrates a new algorithm for noncoherent integration and ambiguity resolution in medium PRF wave-forms. Range and Doppler ambiguity resolution is one of the main issues in Medium PRF radars [1,2,3]; it will be shown that the proposed algorithm provides range and Doppler ambiguities resolution as an inherent feature while maximizing detection probability with respect to conventional binary integration. The algorithm is described and tested by means of a numerical examples, in which non ideal radar accuracies and target cell migration are considered and managed with a proper clustering technique. The resulting design of the algorithm shows high robustness to the aforementioned sources of error affecting radar measurements.

Fusion of tri-dimensional surveillance radar data

The paper deals with the problem of impact point prediction of ballistic targets (BT) by processing measurements acquired by two 3D surveillance radars. It is assumed that the radars acquire a limited number of measurements that do not encompass the whole target trajectory; thus the established target track has to be extrapolated ahead in time in order to predict the coordinates of the impact point. The updating and testing of the data extractor (DE) of a notional tri-dimensional surveillance radar system is presented in this paper; the modified hardware and software is capable of acquiring, managing and fusing tracks pertaining to the radar system housing the DE and to other systems connected to the DE itself

FM-based passive radar: Height estimation with Doppler measures

Purpose of the paper is to present a solution for the target height estimation problem for multi-frequency multi-static passive radar. Aim of the proposed estimation strategy is to provide 2D passive sensors, which measure only bistatic range and Doppler, with target height estimation capability via the simultaneous exploitation of multiple FM transmitters (88–108 MHz). Results achieved with simulated and real passive data demonstrate that it is possible to estimate the target height with an accuracy of few hundreds of meters even if the precision of bistatic range measures is poor (up to one kilometer); this is possible thanks to the bistatic Doppler measures that show a standard deviation of few or fraction of Hz. The above mentioned result is not available in open technical literature- as far as we know- and it is covered by European patent EP2656101B1 and Italian patent no. 0001418266.

Closed formulas for evaluating radar monopulse accuracy

Monopulse is a widely used algorithm to estimate the target angular co-ordinates in radar application. Formulas exist that give approximate values for the accuracy achievable with monopulse. This paper derives simple but accurate closed formulas to estimate the monopulse accuracy by taking into account the radar detection threshold (and then PD and Pfa) and the target fluctuation models.

Adaptive waveforms selection for IMM-UKF tracking architecture: application to multifunctional radar systems in heavy cluttered scenario

Modern phased array radars are able to adaptively manage the way in which they explore the surroundings, both in the space domain (thanks to their beam steering capability) and in the time domain (via a smart selection of convenient waveforms), in order to suit a variety of environments. Multifunction radars, more than tracking radars, are in big need of an efficient way to allocate their limited resources (namely, the radar time) to a number of tasks, so that being adaptive is not only a boost for the tracking performances, but also a way to spare resources during undemanding tasks (i.e. big targets in clear areas) and reroute them towards more difficult ones.