Title :
Maximum likelihood estimation for array processing in colored noise
Author :
Nagesha, Venkatesh ; Kay, Steven
Author_Institution :
Dragon Syst. Inc., Newton, MA, USA
fDate :
2/1/1996 12:00:00 AM
Abstract :
Direction of arrival estimation of multiple sources, using a uniform linear array, in noise with unknown covariance is considered. The noise is modeled as a spatial autoregressive process with unknown parameters. Both stochastic and deterministic signal models are considered. For the random signal case, an approximate maximum likelihood estimator of the signal and noise parameters is derived. It requires numerical maximization of a compressed likelihood function over the unknown arrival angles. Analytical expressions for the MLEs of the signal covariance and the AR parameters are given. Similar results for the case of deterministic signals are also presented
Keywords :
autoregressive processes; covariance analysis; direction-of-arrival estimation; linear antenna arrays; maximum likelihood estimation; noise; random processes; stochastic processes; AR parameters; MLE; approximate maximum likelihood estimator; array processing; arrival angles; colored noise; compressed likelihood function; deterministic signal model; direction of arrival estimation; maximum likelihood estimation; multiple sources; noise parameter; numerical maximization; random signal; signal covariance; signal parameters; spatial autoregressive process; stochastic signal model; uniform linear array; Array signal processing; Autoregressive processes; Colored noise; Covariance matrix; Finite impulse response filter; Maximum likelihood estimation; Noise reduction; Parameter estimation; Signal processing algorithms; Statistics;
Journal_Title :
Signal Processing, IEEE Transactions on
