Stochastic Model of Terrain Effects Upon the Performance of Land-Based Radars

Abstract

A stochastic model of land clutter visibility and of terrain screening of targets, with particular application to low-flying targets under surveillance by a microwave land-based radar system, is described. The model is non-site-specific, but detailed. It allows radar performance measures such as the mean length of track to be obtained analytically, without averaging large numbers of site-specific simulations or requiring high fidelity terrain data. The trajectories of terrain-following targets are described in terms of ensembles of Markov processes. The main dependencies of the model are on: - terrain relief; - radar height; - target altitude; - distance of closest approach between the target and the radar. The model can be used to generate simulated clutter maps and target screening diagrams, and indeed this is done to compare the model results with experimental data. However, the main aim is to predict the effects of target screening and land clutter directly from the model, rather than through large numbers of simulations. The equations which can be used to derive such predictions are given, and applied to a simple case: the time at which an incoming target first enters a cluttered cell. This approach to such calculations is extremely computationally efficient.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1991
Accession Number
ADP006395

Entities

People

  • M. A. Wood
  • S. P. Tonkin

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Aircrafts
  • Detection
  • Differential Equations
  • Distribution Functions
  • Earth Models
  • Equations
  • Gaussian Distributions
  • Kolmogorov Equations
  • Markov Processes
  • Models
  • Normal Distribution
  • Partial Differential Equations
  • Probability
  • Probability Distributions
  • Radar
  • Simulations
  • Terrain Following

Readers

  • Computational Modeling and Simulation
  • Geodesy
  • Sensor Fusion and Tracking Systems.