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A sensitivity analysis is developed for a direction of arrival (DOA) based source localization method in an Underwater Wireless Sensor Array Networks (UWSAN). It is assumed that each sensor array in a UWSAN will yield an estimate of directions of arrival of underwater acoustic sources (DOAs). By collecting all DOAs in a fusion center, a least square estimate of the location of each target may be obtained...
The matched filter, as a popular method, has been widely used to image a target in the radar society. Nevertheless, there exists an important difficulty that the resolution of the image produced by the filter can be changed with the variation of the target's distance. In this paper a distinct imaging algorithm through the exploitation of the sparsity of the received echoes is presented for the multiple-input...
The back-projection (BP) algorithm is a popular imaging method. Nevertheless, there exists a difficulty that the cross-range resolution acquired by the standard BP algorithm is dependent on the bandwidth of transmitted signal when the BP algorithm is directly used to the multiple-input multiple-output (MIMO) radar for imaging a target in the cross-range direction without any variation. In this paper,...
With novel underwater wireless sensor array network (UWSAN) architecture that consists of multiple distributed arrays of acoustic sensors, maximum likelihood localization based on acoustic energy is proposed for solving the source localization in underwater and low signal to noise ratio. The exactly maximum likelihood (ML) target location estimator is derived. Very impressive simulation results demonstrated...
With novel underwater wireless sensor array network architecture, the weighted least square (WLS) source localization method is developed. In this method, each sensor node is attached to a local sensor array which can estimated Signal-Noise-Ratio (SNR) as well the local direction-of-Arrival (DOA). Global localization can combined with estimated DOA selected by SNR. The target position can be fused...
To reduce the hardware complexity which is aroused by the limitation of sampling theory because of the use of the frequency-domain method, a wide-band MIMO imaging method based on a symmetrical exponential distribution nonlinear array is proposed. Compared to the uniform linear array, this given exponential distribution nonlinear array has the lower sidelobe level and better imaging performance. Furthermore,...
In novel underwater wireless sensor array network architecture (UWSAN), each sensor node is attached to a local sensor array which performs maximum likelihood direction of arrival (DOA) locally. Sensor nodes communicate via acoustic channel and exchange DOA estimate and received target signal energy. Global DOA based localization is combined with energy in a non-linear least square cost function to...
A novel underwater wireless sensor array network architecture is proposed. In this wireless sensor network, the maximum likelihood estimate of target location based on amplitude and phase of acoustic signatures is developed. Each local likelihood function can be partitioned into the amplitude and phase portion. For each sensor node is attached to a local sensor array which can performs maximum likelihood...
Up to now, it still remains a big challenge for us to build a high performance geo-computing system with high processing speed and also be easy of use by domain researchers. The unprecedented scale data and various complex algorithms pose many computational and management challenges. To properly settle these main issues above, a new system framework for high performance geo-computing is presented...
In this paper we propose an imaging method via wideband multiple-input multiple-output radar to reduce the hardware complexity of the system. Since a spatial parallel procedure to sample the scattered echoes during a single snapshot illumination, instead of the spatial sequential sampling procedure during multiple snapshot illuminations in classical ISAR imaging, is utilized in our method, the complex...
Parallel and adaptability are introduced in the algorithm of quantum-behaved PSO in this paper, which is named PAQPSO and used to solve the CO problem. The PAQPSO outperforms QPSO and AQPSO in global search ability and local search ability, because the parallel and adaptive method is more approximate to the learning process of social organism with high-level swarm intelligence and can make the population...
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