Hughes Aircraft Company

Hughes Electronics Corporation

Leo H Hui

Michael W Autry

Roy T Okida

A range cell formation process that are used to enhance the quality of an image following a perspective transformation from range-azimuth coordinates (B-scan) into elevation-azimuth coordinates (C-scan). The present range cell formation process eliminate situations where there are missing data points at the far range, and large areas that have the same data point at the near range. The range cell formation process evaluates the data content in range cells on a case by case basis using a prioritized system to determine what is to be displayed so that a high level of image contrast is maintained. In the far range, range cell data that are in between range points defined by every two adjacent elevation points are processed and a priority system is used to determine the best intensity value to use for the elevation points. The priority system is such that bright objects have the highest priority, followed by dark objects, and then followed by an average background level. Range cells are processed to determine which priority is met, and then the appropriate intensity is used. If a bright object is detected in the range cells, then the maximum intensity of the range cells is used. If a dark object is detected, then the lowest intensity of the range cells is used. Otherwise, the average intensity of the range cells is used. In the near range, no enhancements are made to reduce the size of large areas, but the size of bright objects is reduced, thereby providing a sense of increased focus in the near range.

Range cell formation processing

A high speed and high precision coordinate transformation process for transforming image data in range-azimuth coordinates to horizontal-vertical display coordinates. The process is comprised of the following steps. Recursion initialization parameters and values for a perspective transformation are computed. Then, range and azimuth values using predetermined recursion equations are computed. A critical range factor using predetermined recursion equations and inverse operation is computed. Range and azimuth results are computed. Display address values are computed. Data is retrieved and the data is stored in display locations. A decision is then made whether the last display address has been stored. Additional display address values are computed until all addresses have been computed, and the process is ended once all addresses have been computed. The process is particularly suited for radar or lidar data, which is typically collected in B-scan format, and transforms the data into a virtual image on a head-up type display , which is in C-scan format. The process takes a display pixel in display coordinates and computes corresponding range and azimuth coordinates. The process uses a recursive form of a 2nd order Taylor series approximation, combined with a precise range calculation term in order to get the high precision and high speed performance. The use of the 2nd order Taylor series approximately allows the matrix calculations to be done at frame initialization for the first pixel and the subsequent pixel to pixel calculations to performed as an incremental addition to the initial values. The use of the recursive form of the approximation reduces the pixel incrementing calculations from nineteen operations per pixel to four operations per pixel. The precision range calculation requires four operations per pixel.

Precision high speed perspective transformation from range-azimuth

A monopulse thresholding processor and method for improving resolution by using the difference channel data to eliminate 'excess' sum channel returns. The processor may be used with a radar system that comprises an antenna, a transminer, a receiver for processing transmitted radar signals to produce radar returns therefrom, a log compressor for converting radar returns to log values, and a display for displaying the radar returns. The signal processor comprises a left sum and right sum generator coupled to the receiver for computing a left sum and a right sum from radar returns generated by the receiver. A pseudo-difference generator is coupled to the left sum and fight sum generator for generating pseudo-difference channel data. A beam sharpener is coupled to the left sum and right sum generator and to the pseudo-difference generator for beam sharpening the radar returns. A minimums generator coupled between the left sum and right sum generator and the beam sharpener for processing outputs from the left sum and right sum generator, for comparing them to a threshold value, and for providing an output signal comprising a minimum of the processed radar returns. The present invention generates a pseudo-difference channel using sum channel dam, thereby reducing hardware and software, and uses the difference channel as a threshold for keeping the sum channel returns. The sum channel returns are not modified by the difference channel returns if the threshold is exceeded. Therefore, sidelobes resulting from intermixing of the sum and difference channel returns are not possible, thereby eliminating generation of false targets. Also, because sum channel returns that exceed the threshold are not modified, these signals remain at their original strength. The present invention uses the pseudo difference channel data as a threshold on the sum channel data to perform beam sharpening that sharpens discrete target and clutter edges.

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Los Angeles, CA, United States of America

Leo H Hui