Radar apparatus using neural network for azimuth and elevation d

Details Radar apparatus using neural network for azimuth and elevation d Radar apparatus using neural network for azimuth and elevation d

1993-01-12

1994-09-06

MacDonald, Allen R.

Communications: directive radio wave systems and devices (e.g.,

Clutter elimination

Mti

342350, G06F 1518

Patent

active

053455398

DESCRIPTION:

BRIEF SUMMARY
BACKGROUND OF THE INVENTION

1. Field of the Invention
This invention relates to radar-apparatus and more specifically to radar apparatus for point source location.
2. Discussion of Prior Art
Simple radar apparatus transmits a narrow (or searchlight) beam and where the transmitted beam is returned and received, this indicates the presence of a target (or source) within the path of the searchlight beam. Angular position of the beam gives azimuthal and height co-ordinates of the source, whilst time of flight (i.e. time between transmitting and receiving a signal) gives a distance co-ordinate for the source.
One requirement of radar apparatus is the accurate position estimation of point sources. Such estimation requires measurement of distance and angular position. Distance is quite easily measured by time of flight, but angular position measurement is more difficult. Conventionally there are two stages in the accurate angular position estimation of a point-source. These are performed by surveillance radar, which provides detection and rough angular position estimation of a point source and tracking radar, which is used to provide an accurate angular position estimate.
The most popular current form of tracking radar is the monopulse type. This usually forms a mechanically steered antenna having a group of four beams on receive. A point-source is tracked in elevation and azimuth by maintaining the position in the centre of the cluster of beams (M. I. Skolnik, Introduction to Radar Systems, McGraw-Hill Book Company, New York, Second Edition, 1980).
Phased arrays or electronically steered antennas, either linear or planar arrays, provide an alternative to the mechanically steered antenna. Such arrays are formed by e.g. a x, y matrix of separate radiating or receiving elements. A beam is steered by independently varying the phase of signals applied to each radiating element in the array of radiating elements. One of the advantages of a phased array is the ability to generate a single or multiple beams simultaneously from the same array by connecting the elements into a single or different groups. These beams may be steered independently, or as a group as in monopulse, and it is often convenient to transmit a wide radiating pattern, encompassing the field of view of a cluster of the multiple receive beams. Accurate angular position estimation of the point-source is achieved by adjusting the phases so that a point-source remains in the centre of the cluster, so that processing similar to monopulse may be applied. However, a major disadvantage of this systems lies in the fact that each radiation element requires phase adjusters and associated addressing equipment. This makes phased array systems very expensive.
A different approach for receiving is that of measuring the output of each receiving detector element and to perform signal processing on each receiving detector element. A focal-plane array operates with fixed beams and although it is possible to achieve easily an estimate of the angular position of the point-source in the scene by considering the largest output of the array of receivers, more accurate angular estimation of position requires further processing. There are no standard approaches published in the literature for processing the outputs of a fixed multibeam system, either for focal-plane or for planar array systems, to give the accuracy provided by the monopulse system. However, one method which gives estimates of angular position with nearly the same accuracy as a monopulse system is based on a maximum likelihood approach. With this approach, the signal processing must be characterised by a calibration which gives a set of known responses of the array to targets at given positions. The calibration may be viewed as some form of training of the system (e.g. I. J. Clarke, "Comparison of Advanced Signal Processing Algorithms", Eurocon 1986, Paris).
The training may be achieved by moving a single source around in the far field of the observed scene of the sensors and recording the output of the system

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