Direction of arrival

This paper presents a unified framework, based on the generalized likelihood (GL), for the detection of targets and the estimation of their direction of arrival (DoA), when operating with modern radar systems that have general antenna array configurations, which contain a mixture of high- and low-gain beams. Adaptive processing structures are presented to remove both side lobe and main lobe

A new method for estimating the direction-of-arrival (DOA) of unknown number of source signals is proposed. The angular directions of coherent and/or noncoherent signals are estimated by controlling the nulls of the antenna array factor. A genetic algorithm is used to find the nulls on the unit circle that minimize the array output power. The pseudo-spectrum is obtained by rotating the nulls on the unit circle and estimating the corresponding array output power. The simulation results indicate that the direction-of-arrivals are estimated accurately in the presence of a wide range of input noise levels.

The technique for estimating the parameters of multiple waves provides a convenient tool for the analysis of multiple-waves fields and eventually for actual applications to mobile communications. Based on the extended Kalman filter (EKF), we analyze a recursive procedure for 2-dimensional directions of arrival (DOA) estimation and we will employ the two-L-shape arrays. A new space-variable model which we call a spatial state equation is presented using array element locations and incident angles. In this paper we briefly recapitulate the most important features of the extended Kalman filter (EKF). The performance of the proposed approach is examined by a simulation study with three signals model. The simulation results show a good estimate performance.

The technique of interpolated arrays is applied to ESPRIT-type direction finding methods. The resulting method uses sensor arrays with an arbitrary configuration, thus eliminating the basic restrictive requirement of ESPRIT for two (or more) identical arrays. This approach allows for resolving D+1, while the original ESPRIT method requires at least 2D sensors. Moreover, it is shown that while ESPRIT performs poorly for signals propagating in parallel (or close to parallel) with the array displacement vector, the advocated technique does not exhibit such weakness. Finally, using two subarrays, ESPRIT cannot resolve azimuth and elevation even when the sensors are not collinear. However, the interpolated ESPRIT procedure resolves azimuth and elevation using only a single array. The performance of the original ESPRIT when the sensor locations are perturbed is also discussed and illustrated numerically

Multi-channel self-steering microphone arrays for hearing aid ap- plications enable the hearing impaired user to follow conversa- tions coming from other directions than the front direction. Bin- aural connections between left and right hearing aids allow for (i) the estimation of the direction of arrival (DOA) and thus for auto- matic beam-steering, (ii) a higher noise reduction due to a greater number of sensors, and (iii) the preservation or reconstruc tion of binaural cues that can be used by the hearing impaired listener for object segregation. Since the microphones are placed near the human head, diffraction and shadowing effects have to be in- corporated into the beamformer design as well as into the DOA estimator. In this contribution a combined system of DOA estimation and a head-worn 6-channel binaural noise reduction scheme is pre- sented and evaluated using perceptual measures that are based on auditory models.

This paper focuses on the stochastic Cramer-Rao bound (CRB) for the direction of arrival (DOA) for binary phase-shift keying (BPSK) and quaternary phase-shift keying (QPSK) modulated signals observed on the background of nonuniform white noise with an arbitrary diagonal covariance matrix. Explicit expressions of the CRB for the DOA parameter alone in the case of a single signal waveform is

This paper deals with direction of sound wave arrival determination using time-delay estimation and beamforming methods with utilization of static microphone array with fixed geometry configuration. Theoretical part describes main principle of both methods and possibility of program implementation. Experimental part proposes hardware design of the sensory systems separately for time-delay estimation and beamforming evaluation methods due to different requirements on microphone array structure. Developed localization system is based on standard personal computer equipped with Advantech PCI-1716 multichannel data acquisition device.

In this paper we propose a complete computational system for Auditory Scene Analysis. This time-frequency system localizes, separates, and spatializes an arbitrary number of audio sources given only binaural signals. The localization is based on recent research frameworks, where interaural level and time differences are combined to derive a confident direction of arrival (azimuth) at each frequency bin. Here, the