A target tracker using spatially distributed infrared measurements
Abstract
An extended Kalman filter algorithm is designed to track a point source target in an open-loop tracking problem, using outputs from a forward-looking infrared (FLIR) sensor as measurements. A Monte Carlo analysis is conducted to determine the performance of the filter as a function of signal-to-noise ratio, target spot size, the ratio of rms target motion to rms atmospheric jitter, target correlation times, and mismatches between the true target spot size and the size assumed by the filter. The performance of the extended Kalman filter is compared to the performance of an existing correlation tracker under identical conditions.
- Publication:
-
IEEE Transactions on Automatic Control
- Pub Date:
- April 1980
- Bibcode:
- 1980ITAC...25..222M
- Keywords:
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- Flir Detectors;
- Kalman Filters;
- Laser Applications;
- Optical Tracking;
- Remote Sensors;
- Target Acquisition;
- Correlation Detection;
- Monte Carlo Method;
- Optical Radar;
- Performance Prediction;
- Signal To Noise Ratios;
- Instrumentation and Photography