HF direction finding by wave front testing in a fading signal environment
Abstract
Calculations are reported of the probability of observation of various degrees of phase front nonlinearity, for two and three signals incident from different directions upon a phasemeasuring array. It is assumed that the signals fade independently and that their amplitude probability densities are described by a Rayleigh law. The measure of phase front nonlinearity employed is the rms deviation from the best straightline fit to the measured phases along a linear array. The worstcase condition is that of equal average powers in the incident signals. When there are two such signals present, it is shown that the probability is 0.5 that a single observation of the rms phase deviation will yield a result of 25° or less. When there are three equalpower signals present, the corresponding probability is 0.2. Experimental measurements over a 911km midlatitude path and a 2100km auroralzone path confirm the general behavior predicted by the theory. The experimental program included concurrent measurements using FMCW, CW, and singlesideband signals from a controlled transmitter. The range resolution capability of the FMCW signals was utilized to provide directionofarrival statistics on a modeseparated basis. The standard deviation of the direction of arrival varied from 0.3° for E mode signals to 1.4° for F_{2} highangle signals. The CW and singlesideband signals were processed by selecting only those phase fronts with rms phase deviations of 10° or less. For these, directionofarrival standard deviations were in the range 0.6°0.9° with slightly smaller deviations being observed for the CW signals.
 Publication:

Radio Science
 Pub Date:
 August 1982
 DOI:
 10.1029/RS017i004p00827
 Bibcode:
 1982RaSc...17..827R
 Keywords:

 High Frequencies;
 Propagation Modes;
 Radio Direction Finders;
 Signal Fading;
 Single Sideband Transmission;
 Wave Fronts;
 Continuous Radiation;
 Linear Arrays;
 Nonlinearity;
 RootMeanSquare Errors;
 Signal Processing;
 Standard Deviation;
 Communications and Radar