Direction-of-arrival estimation in applications with multipath and few snapshots

This paper analyzes two direction-of-arrival (DOA) estimation algorithms used in the presence of multipath propagation and with very few snapshots. The conditional maximum likelihood (CML) algorithm and the method of direction estimation (MODE) are discussed. The estimates provided by these algorithms are shown to coincide for large number of snapshots or large signal-to-noise ratio. Necessary and sufficient conditions are derived for the algorithms to yield unique estimates. It is shown that their uniqueness conditions coincide with the minimal uniqueness condition on the array, that is independent of the algorithm used (if the array does not satisfy this minimal condition, no DOA estimation method can give unique estimates). Numerical examples are presented to demonstrate the theoretical results.The work of A. Nehorai and D. Starer was supported by the Air Force Office of Scientific Research under Grant No. AFOSR-90-0164 and by the Office of Naval Research under Grant No. N00014-91-J-1298.     

Evaluation and management of urinary incontinence in older patients

The training of health care providers in the diagnosis and management of urinary incontinence is inadequate, and evaluation and management skills are less than optimal. Urinary incontinence volume measurement is difficult to perform accurately in elderly long-term-care inpatients. After incontinence has been noted, the physician needs to select the appropriate studies to determine the cause and choose the correct treatment. Otherwise, treatable causes such as outlet obstruction or fecal impaction may be missed. Subsequent management includes scheduled visits to the toilet, treatment of impaired mobility, use of easily identified and accessible toilet facilities, reevaluation of the need for restraints and side rails, and, if appropriate, the use of drugs to treat the incontinence. Many elderly incontinent patients who are treated in the outpatient setting can be cured or substantially improved.     

Newton algorithms for conditional and unconditional maximumlikelihood estimation of the parameters of exponential signals in noise

The authors present polynomial-based Newton algorithms for maximum likelihood estimation (MLE) of the parameters of multiple exponential signals in noise. This formulation can be used in the estimation, for example, of the directions of arrival of multiple noise-corrupted narrowband plane waves using uniform linear arrays and the frequencies of multiple noise-corrupted complex sine waves. The algorithms offer rapid convergence and exhibit the computation efficiency associated with the polynomial approach. Compact, closed-form expressions are presented for the gradients and Hessians. Various model assumptions concerning the statistics of the underlying signals are considered. Numerical simulations are presented to demonstrate the algorithms' performance     

Passive localization of near-field sources by path following

A new algorithm for passively estimating the ranges and bearings of multiple narrow-band sources using a uniform linear sensor array is presented. The algorithm is computationally efficient and converges globally. It minimizes the MUSIC cost function subject to geometrical constraints imposed by the curvature of the received wavefronts. The estimation problem is reduced to one of solving a set of two coupled 2D polynomial equations. The proposed algorithm solves this nonlinear problem using a modification of the path-following (or homotopy) method. For an array having m sensors, the algorithm reduces the global 2D search over range and bearing to 2(m-1) independent 1D searches. This imparts a high degree of parallelism that can be exploited to obtain source location estimates very efficiently