Diffraction Analysis and Tactical Applications of Signal Propagation Over Rough Terrain
Abstract
The free space propagation model is inadequate to predict the mean path-loss in ground wireless communication. Also, many existing propagation channel models do not adequately predict path-loss in rough terrain because most of them were based on measurements in urban areas. Hence, a channel model that estimates mean path-loss over many different kinds of terrain conditions is desired. In this thesis, two new propagation channel models, Real Terrain Diffraction Model (RTDMOD) and Universal Terrain Channel Model (UTCMOD), were developed. Other geometric theory of diffraction (GTD) methods (Epstein-Peterson (EP) and Deygout (DG)) agree within 5 % from 3 MHz to 3GHz with RTDMOD. However, unlike these other methods, RTDMOD can account for an almost unlimited number of obstacles and has the advantage of predicting the significant diffraction point locations as well as the total path-loss for a given set of real terrain data. The computationally efficient stochastic channel model, UTCMOD, was developed from numerous Monte Carlo simulations using RTDMOD. UTCMOD agrees within 1 dB/km over a broad carrier frequency range and a large terrain height variance range with the popular Hata model. Furthermore, UTCMOD is applicable to many different kinds of terrain conditions whereas the Hata model is most relevant for terrain conditions characteristic of large cities or medium-small cities. Unlike previous models, UTCMOD considers communication link conditions (i.e the relative heights of transmitter, receiver, and terrain peaks along the path) and provides the correct perspective for analyzing the propagation effects. Also UTCMOD can be used to optimize many tactical communication (TAC COMM) and electronic warfare (EW) scenarios for Low Probability of Interception (LPI) performance.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 1997
- Accession Number
- ADA327900
Entities
People
- You-cheol Jang
Organizations
- Air Force Institute of Technology