Composite stochastic model for clutter
Abstract
Radar clutter has been modeled using several different probability density functions. Autocorrelation functions of clutter based on each of these density functions have been evaluated. Autocorrelation function of time series data is evaluated by determining the coefficients of the time series using an adaptive scheme through an FIR filter. The coefficient of the time series is determined using a system identification technique. This procedure helps identify the autocorrelation of unknown clutter obtained from a radar data-platform. This procedure also enables development of a likelihood ratio test for radar detection, based on the rates of autocorrelation/auto covariance of signal plus noise and noise, respectively.
- Publication:
-
Noise and Clutter Rejection in Radars and Imaging Sensors
- Pub Date:
- 1990
- Bibcode:
- 1990ncrr.symp...21R
- Keywords:
-
- Clutter;
- Probability Density Functions;
- Radar Detection;
- Signal To Noise Ratios;
- Stochastic Processes;
- Autocorrelation;
- Matched Filters;
- Maximum Likelihood Estimates;
- System Identification;
- Time Series Analysis;
- Communications and Radar