HIGH RESOLUTION NONCOHERENT RADAR IMAGER

Patent №

US 4,707,697

Granted

1987-11-17

Filed 1986

Owner

HONEYWELL INC.

Lab

AI components

2

vision · planning

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

06858812

In accordance with a first arrangement, a non-coherent, pulse radar transmitter emits N-sequential signals of differing frequencies at predetermined time intervals, the transmitted pulses being directed toward a given target area of interest. Further included is a radar receiver for detecting and processing the composite radar return signal samples of N differing frequencies which are reflected from a plurality of point scatterers located in the area of interest. The varying D.C. interference signal of the plural radar return signal samples occasioned by the differing frequencies are detected and a one-dimensional Fourier transformer is performed on that composite radar return signal samples to facilitate target identification. A programmed processor is used to dervie a plurality of feature characteristics from the Fourier transform of the detected radar return signals and the features so computed are compared with features characteristic of known potential targets on a best-match basis. In accordance with an alternative embodiment, a system is provided which can extract two-dimensional, high-resolution information from radar return signals in which the non-coherent pulse radar means is moved from one location to another with respect to a target area of interest while transmitting N-sequential signals of differing frequencies at predetermined time intervals. The radar receiver is positioned to detect and range gate composite radar return signal samples reflected from a plurality of point scatterers and once a time varying D.C. interference signal is detected, a two-dimensional Fourier transformation is performed on that composite signal.

VisionPlanningG01S 13/90G01S 7/292G01S 7/412G01S 13/66G06T 3/4084

AI classification

Planning0.98
Vision0.97
AI hardware0.01
Knowledge representation0.00
Evolutionary computation0.00
Machine learning0.00
Natural language0.00
Speech0.00

Ownership

HONEYWELL INC.

assignment · 45580582

Assignors

COULTER, THOMAS R., ISAACSON, PHILIP O., THIEDE, EDWIN C.

On an employer assignment, the assignors are typically the inventors.

From the same owner

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