Estimation of radio refractivity structure using matched-field array processing

Abstract

In coastal regions the presence of the marine boundary layer can significantly affect RF propagation. The relatively high specific humidity of the underlying "marine layer" creates elevated trapping layers in the radio refractivity structure. While direct sensing techniques provide good data, they are limited in their temporal and spatial scope. There is a need for assessing the three-dimensional (3-D) time-varying refractivity structure. Recently published results (Gingras et al.[1]) indicate that matched-field processing methods hold promise for remotely sensing the refractive profile structure between an emitter and receive array. This paper is aimed at precisely quantifying the performance one can expect with matched-field processing methods for remote sensing of the refractivity structure using signal strength measurements from a single emitter to an array of radio receivers. The performance is determined via simulation and is evaluated as a function of: 1) the aperture of the receive array; 2) the refractivity profile model; and 3) the objective function used in the optimization. Refractivity profile estimation results are provided for a surface-based duct example, an elevated duct example, and a sequence of time-varying refractivity profiles. The refractivity profiles used were based on radiosonde measurements collected off the coast of southern California.

Estimation of Surface Duct Using Ground-Based GPS Phase Delay and Propagation Loss

“…The Bartlett objective function, which is broadly used in the field of marine acoustic tomography, achieves good results in estimating refractivity conditions [10]. Hence, we adopted the Bartlett power function as the new cost function.…”

“…However, the ordinary least-squares (OLS) function cannot be minimized directly when the parameters acquire small errors in some cases. The Bartlett objective function, which is broadly used in the field of marine acoustic tomography, achieves good results in estimating refractivity conditions [10]. Hence, we adopted the Bartlett power function as the new cost function.…”

“…Hence, we adopted the Bartlett power function as the new cost function. Referring to Gerstoft et al [10], the objective function is defined as: N is the range, and element N is the number of GPS receivers at the same antenna height. Here, the receiver heights are 20 m, 50 m, 100 m, 150 m, and 400 m. There is only one receiving antenna at a given height level.…”

“…The methods of sounding refractivity profiles-such as radiosondes, microwave refractometers, and evaporation duct sensors-have been developed [10][11][12][13][14]. However, these methods are direct sensing techniques and have lower sparse sampling rates.…”

“…A promising approach for sensing refractivity profiles remotely is the use of Global Positioning System (GPS) signals [10,26]. Hitney [27] demonstrated the capability of estimating the trapping layer's base height from ultrahigh frequency (UHF) signal strengths.…”