초록 ▼

The present invention provides for a method for maximum likelihood estimation of bearings. This method of the present invention utilizes a novel maximum likelihood algorithm which can be employed to process one or two dimensional array data. The method is applicable to radar and sonar direction-of-a

The present invention provides for a method for maximum likelihood estimation of bearings. This method of the present invention utilizes a novel maximum likelihood algorithm which can be employed to process one or two dimensional array data. The method is applicable to radar and sonar direction-of-arrival estimation problems.

대표청구항 ▼

A method of estimating parameters from sensor outputs, said method implementing the steps of: (a) sampling and digitizing said sensor outputs; (b) forming a sample covariance matrix from said sampled and digitized outputs of said sensors; (c) averaging the diagonals of said sample covariance matrix;

A method of estimating parameters from sensor outputs, said method implementing the steps of: (a) sampling and digitizing said sensor outputs; (b) forming a sample covariance matrix from said sampled and digitized outputs of said sensors; (c) averaging the diagonals of said sample covariance matrix; (d) averaging diagonals of said sampled covariance matrix for obtaining a sample covariance vector (Rm); (e) providing a projection vector (Pm) where [Figure] [Figure] [Figure] for kn to be the parameter of the nth source; (f) computing a likelihood function (L) by multiplying said sample covariance vector with said projection vector; (g) maximizing said likelihood function with respect to said parameters; (h) resulting said parameters at said maximum for providing a best estimate of parameters.