Multichannel System Identification and Detection Using Output Data Techniques
Abstract
In multichannel identification and detection (or model-based multichannel detection) problems the parameters of a model are identified from the observed channel process, and the identified model is used to facilitate the detection of a desired signal in the observed process. A model-based multichannel detection algorithm was developed in the context of an innovations- based detection algorithm (IBDA) formulation for surveillance radar system applications. The state space model class was adopted to model the vector channel process because it is more general than the time series model class used in most analyses to date. An IBDA methodology was developed based on an algorithm which uses output data directly and offers computational and performance advantages over alternative techniques. A computer simulation was developed to validate the methodology and the algorithm, and to carry out performance assessments. Simulation results indicate that the algorithm is capable of discriminating between the null hypothesis (clutter plus noise) and the alternative hypothesis (signal plus clutter plus noise). In summary, the applicability of the approach to radar system problems has been established.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 1993
- Accession Number
- ADB176689
Entities
People
- Dennis W. Davis
- Jaime R. Roman