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Hybrid Kalman Particle Filter for Ground Target Tracking

Award Information

Agency:
Department of Defense
Branch:
Air Force
Award ID:
67734
Program Year/Program:
2005 / SBIR
Agency Tracking Number:
F041-204-2013
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
Sigtem Technology, Inc.
1343 Parrott Drive San Mateo, CA -
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 2
Fiscal Year: 2005
Title: Hybrid Kalman Particle Filter for Ground Target Tracking
Agency / Branch: DOD / USAF
Contract: FA8650-05-C-1808
Award Amount: $749,942.00
 

Abstract:

We propose to continue our Phase I efforts by demonstrating the class of hybrid Kalman particle filters (HKPF) for tracking ground targets on road in Phase II. In the proposed formulation, the road network is represented with one-dimensional (1D) models. This 1D modeling simplifies the target kinematics considerably and reduces the size of the target state space by up to ¿, which directly translates into the computation and memory savings "desperately" needed by particle filters. It also allows for explicit incorporation of the road information and interactions with other targets into the filters. Together with features aiding from HRRR and/or SAR (simulated from FATSO in Phase II), it provides additional means for better report-to-track association and tracking of targets across an intersection (move-stop-move with or without turn). Furthermore, the measurement nonlinearity arising from the 1D modeling of roads and target feature aiding is well handled by the proposed nonlinear filters. In Phase II, the computational algorithms developed in Phase I will be implemented into well-structured software modules toward a software development toolkit as part of the Phase II deliverable and a "marketable" product to pursue after Phase II. At the same time, we will decompose the nonlinear tracking filters into pipelined parallel structures and implement it in a Mercury RACE++ Series multiprocessor platform for demo.

Principal Investigator:

Chun Yang
Principal Scientist
2155139477
chunyang@sigtem.com

Business Contact:

Chun Yang
President
2155139477
chunyang@sigtem.com
Small Business Information at Submission:

SIGTEM TECHNOLOGY, INC.
113 Clover Hill Lane Harleysville, PA 19438

EIN/Tax ID: 233012783
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No