ARCHITECTURES

Award Information
Agency:
Department of Defense
Branch
Army
Amount:
$58,704.00
Award Year:
1986
Program:
SBIR
Phase:
Phase I
Contract:
n/a
Award Id:
4460
Agency Tracking Number:
4460
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
1065 E Brokaw Rd, San Jose, CA, 95131
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
RICHARD H TRAVASSOS
(408) 286-0421
Business Contact:
() -
Research Institute:
n/a
Abstract
TARGET TRACKING AND NAVIGATION EQUIPMENT SUCH AS THE GPS CONTAIN A KALMAN FILTER WHICH EITHER ACTS TO SMOOTH DATA WHEN THE UNIT IS UNAIDED, OR AS AN ESTIMATING FILTER WHEN INERTIAL DATA ARE ACCEPTED. THE NEED TO INTEGRATE MULTIPLE SENSORS RESULTS IN A HYBRID SYSTEM WITH EXTREMELY LARGE COMPUTATIONAL REQUIREMENTS FOR REAL-TIME APPLICATIONS. OFTEN THE HYBRID SYSTEM TAKES THE FORM OF A "CASCADED" FILTER TO EASE THE COMPUTATIONAL BURDEN. SENSOR DATA INTEGRATION IS OFTEN DIFFICULT DUE TO CORRELATING THE TIME OF THE MEASUREMENTS AND THE DIFFERENT MEASUREMENT RATES OF THE SENSORS. IN THIS PROPOSAL, PARALLEL KALMAN FILTER ARCHITECTURES ARE OPTIMIZED FOR HYBRID SYSTEMS CONSISTING OF MULTIPLE SENSORS TO ACHIEVE IMPROVED PERFORMANCE AND STABILITY. THE COMPUTATIONAL ADVANTAGE OF PARALLEL PROCESSING MINI-MIZES MEASUREMENT TIME SENSITIVITY AND DATA TRANSFER OVER THE BUS IN THE SYSTOLIC ARCHITECTURES PROPOSED. THE PARTITIONED SQUARE ROOT AND UPPER DIAGONAL KALMAN FILTER ALGORITHMS PROPOSED ARE CAPABLE OF MULTI-RATE FILTERING VIA A UNIQUE DECOUPLING OF THE PREDICTOR AND CORRECTOR EQUATIONS IN THE FILTER WHILE MAINTAINING OPTIMAL ESTIMATION. THE PARALLEL PROCESSING TECHNIQUES PROPOSED CAN BE EXTENDED TO THE MORE GENERAL CASE OF DISTRIBUTED FILTERING FOR REAL-TIME NAVIGATION, TARGET TRACKING AND SCENE ANALYSIS.

* information listed above is at the time of submission.

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