The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Mar. 20, 1990

Filed:

May. 18, 1987
Applicant:
Inventors:

Nicholas C Donnangelo, Leesburg, VA (US);

John T Abaunza, Warrenton, VA (US);

John G Aiken, Fairfax, VA (US);

Assignee:

Avion Systems, Inc., Leesburgh, VA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G01S / ;
U.S. Cl.
CPC ...
342455 ; 342 32 ; 342 37 ; 342 46 ;
Abstract

An airborne surveillance method and system allows an observer aircraft to determine the position and change of position of a multiplicity of target aircraft and thus allows analysis of collision threats from these aircraft. The system uses a phase comparison direction finding antenna to determine direction of nearby ground based SSRs and all target aircraft of interest. The system further makes use of all other available data including Mode C transponder generated altitude information of the target aircraft, the altitude of the observer aircraft, the received signal strength of both the SSR beam and the received transponder signal, the time difference of arrival between the SSR interrogation signal and the response from the target aircraft, and a variety of other factors to determine the position of the target aircraft. The system compensates for the attitude of the observer aircraft and performs optimal Kalman filtering on the input data set to produce an estimate on target position based upon prior estimates and upon information contained in the data set while making estimates of the error magnitude of each measurement and compensating for these errors. The covariance matrix Q of the Kalman filter is adaptively vaired so as to optimize the estimate of the degree of correlation between various input values.


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