Direction Of Arrival Determination Research Articles

Estimating the direction of arrival of spatially spread sources using block-sparse Bayesian learning with an extended dictionary.

Estimating the direction of arrival (DOA) of spatially spread sources is a significant challenge in array signal processing. This work introduces an effective method within the sparse Bayesian framework to tackle this issue. A spatially spread source is modeled using a multi-dimensional Slepian signal subspace that expands the dictionary and results in a block-sparse structured solution. By taking advantage of block-sparse Bayesian learning, parameter estimation becomes feasible. A complex Gaussian posterior is derived under a multi-snapshot block-sparse framework with a complex Gaussian prior and varying noise conditions. The hyperparameters are estimated using the expectation-maximization algorithm. Through numerical tests and sea test data evaluations, the proposed method shows superior energy focusing for spatially spread signals. Under limited snapshots and challenging signal-to-noise ratios, the current method can still offer precise DOA determination for spatially spread sources.

Narrowband underwater vector sensor using michroelectromechanical systems

A narrowband underwater vector sensor using microelectromechanical (MEMS) systems is demonstrated. A combination of two pressure gradient MEMS sensors and an omnidirectional hydrophone allows for determination of the direction of arrival (DOA) of income sound over 360 degrees azimuth. The MEMS sensors, inspired on the hearing system of the Ormia-ochracea fly, consist of two wings connected by a bridge and anchored to the substrate by a tortional bean. They are operated with open back to allow a cosine dependence with the angle of incidence in the predominant bending vibrational mode. In the vector sensor, two MEMS sensors are orthogonally arranged to provide a cosine and sine directional pattern. When combined with an omnidirectional hydrophone that shares the same phase center, an arctangent estimator is used for DOA determination. The MEMS sensors are operated near resonance to filter out noise coming from undesired bands and improve the signal-to-noise ratio. A correction algorithm is applied to compensate frequency response differences. Two configurations have been demonstrated with the MEMS sensors enclosed in silicone oil and in air. The standard deviation of the measured DOA error has been computed for both configurations to be less than 5 degrees for various types of sound stimuli.

Underdetermined direction of arrival estimation for multiple input and multiple outputs sparse channel based on Bayesian learning framework

Direction of arrival (DOA) estimation for a sparse channel has attracted serious attention recently. Better signal analysis and denoising achieve accuracy in DOA determination. This paper proposes an underdetermined DOA estimation for multiple input and multiple outputs (MIMO) sparse channels. A novel multi-kernel-based non-negative sparse Bayesian learning (MK NNSBL) framework is implemented using the multiplied form of basis vector within the manifold matrix for a defined grid. Meanwhile, virtual antenna locations are reconfigured by exploiting the conventional cuckoo search algorithm (CCSA) for the fine reception of incoming signals on a nonuniform linear array (NULA). The simulated results reveal that the novel approach outperforms in its optimal root mean square error (RMSE) for various signal-to-noise ratio (SNR) limits and the compilation time. The convergence comparative graph indicates the improved performance in the proposed framework over existing algorithms.

Probabilistic analysis of ambiguities in radar echo direction of arrival from meteors

Abstract. Meteors and hard targets produce coherent radar echoes. If measured with an interferometric radar system, these echoes can be used to determine the position of the target through finding the direction of arrival (DOA) of the incoming echo onto the radar. Depending on the spatial configuration of radar-receiving antennas and their individual gain patterns, there may be an ambiguity problem when determining the DOA of an echo. Radars that are theoretically ambiguity-free are known to still have ambiguities that depend on the total radar signal-to-noise ratio (SNR). In this study, we investigate robust methods which are easy to implement to determine the effect of ambiguities on any hard target DOA determination by interferometric radar systems. We apply these methods specifically to simulate four different radar systems measuring meteor head and trail echoes, using the multiple signal classification (MUSIC) DOA determination algorithm. The four radar systems are the Middle And Upper Atmosphere (MU) radar in Japan, a generic Jones 2.5λ specular meteor trail radar configuration, the Middle Atmosphere Alomar Radar System (MAARSY) radar in Norway and the Program of the Antarctic Syowa Mesosphere Stratosphere Troposphere Incoherent Scatter (PANSY) radar in the Antarctic. We also examined a slightly perturbed Jones 2.5λ configuration used as a meteor trail echo receiver for the PANSY radar. All the results are derived from simulations, and their purpose is to grant understanding of the behaviour of DOA determination. General results are as follows: there may be a region of SNRs where ambiguities are relevant; Monte Carlo simulation determines this region and if it exists; the MUSIC function peak value is directly correlated with the ambiguous region; a Bayesian method is presented that may be able to analyse echoes from this region; the DOA of echoes with SNRs larger than this region are perfectly determined; the DOA of echoes with SNRs smaller than this region completely fail to be determined; the location of this region is shifted based on the total SNR versus the channel SNR in the direction of the target; and asymmetric subgroups can cause ambiguities, even for ambiguity-free radars. For a DOA located at the zenith, the end of the ambiguous region is located at 17 dB SNR for the MU radar and 3 dB SNR for the PANSY radar. The Jones radars are usually used to measure specular trail echoes far from zenith. The ambiguous region for a DOA at 75.5∘ elevation and 0∘ azimuth ends at 12 dB SNR. Using the Bayesian method, it may be possible to analyse echoes down to 4 dB SNR for the Jones configuration when given enough data points from the same target. The PANSY meteor trail echo receiver did not deviate significantly from the generic Jones configuration. The MAARSY radar could not resolve arbitrary DOAs sufficiently well enough to determine a stable region. However, if the DOA search is restricted to 70∘ elevation or above by assumption, stable DOA determination occurs above 15 dB SNR.

Application of ESPRIT in broad beam HF ground wave radar sea surface current mapping

HF surface wave radar system OSMAR2000 is a broad-beam sea-state detecting radar. ESPRIT (Estimation of Signal Parameters via Rotational Invariance Technique) algorithm is proposed to apply in DOA (direction of arrival) determination of sea echoes. The algorithm of ESPRIT is briefly introduced first. Then discussions are made on the technique for application in the OSMAR2000 framework. Numerical simulation results are presented to demonstrate the feasibility of radial current mapping based on this method. The algorithm manifests significant performance and computational advantages compared with that of MUSIC. Data acquired by OSMAR2000 are processed to give radial current map and the synthesized vector currents are compared with the in-situ measurement with traditional means. The results show the validity of ESPRIT application in DOA determination for broad-beam radar.

Three-dimensional monopole antenna for direction of arrival determination

The design and realisation of a dodecahedral antenna is investigated. The three-dimensional design with pentagonally shaped faces is described. The simulation program NEC2 (numerical electromagnetics code, version 2) is used to simulate the proposed design. This dodecahedral antenna configuration is optimised for all pertinent parameters, according to the coupling constraints and the radiation pattern. The coupling values and the radiation pattern are measured and compared with the simulated values.