Detection of Point Objects in Spatially Correlated Clutter Using Two Dimensional Adaptive Prediction Filtering
Abstract
This paper studies the performance of a two dimensional least mean square (TDLMS) adaptive filter as a prewhitening filter for the detection of small signals in infrared image data. The spatially broad clutter with long correlation length is seen to be narrowband in the two dimensional frequency domain. This narrowband clutter is predicted and subtracted from the input, leaving the spatially small signal in the residual output. The output energy in the residual and prediction channels of such a filter is seen to depend on the correlation length of the varous components in the input signal, thus permitting the separation of short correlation targets from the longer correlation clutter. False alarm improvements and detection scheme on thermal infrared sensor data with known target points is presented
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1992
- Accession Number
- ADA265862
Entities
People
- James R. Zeidler
- Tarun Soni
- Walter H. Ku
Organizations
- Naval Command, Control and Ocean Surveillance Center