A new nearest-neighbor association approach based on fuzzy clustering

Aziz, Ashraf M.

doi:10.1016/j.ast.2012.02.017

Cited by 34 publications

(19 citation statements)

References 37 publications

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“…5 that the proposed approach successfully associates all the reported tracks and yields satisfactory results. The performance of the proposed method is compared with the performance of Euclidean clustering (Aziz, 2013;Hall, 1992) and conventional fuzzy logic clustering (using IF-THEN rules) (Singh and Bailey, 1997) in a simple example. We consider the case of a single target tracked by a single OTHR in a two ionosphere layers environment.…”

Section: Performance Evaluation and Comparisonmentioning

confidence: 99%

“…The initial state estimates and the corresponding initial covariance matrix are obtained by two points differencing of the measurements with a corresponding covariance matrix as in (Aziz, 2013;Aziz, 2011c). Each target motion is initially in a straight line with constant velocity.…”

Section: Performance Evaluation and Comparisonmentioning

confidence: 99%

“…Some of these applications are diversity communication systems (El-Ansary et al, 2013;Aziz, 2011a), target detection (Aziz, 2010;El-Ayadi et al, 1996), distributed radar surveillance networks (Aziz, 2014c;Aziz, 2008), wireless sensor networks (Aziz et al, 2011;Aziz, 2011b), biomedical applications (El-Badawy et al, 2014;2013) and target tracking (Aziz, 2013;2011c). An association technique is essential processing in multisensor data fusion systems (Hall, 1992).…”

Section: Introductionmentioning

confidence: 99%

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A New Method for Multipath Clustering for Over-the-Horizon Radar

Aziz¹,

Abdelrahman²,

Abouelatta³

2016

American Journal of Applied Sciences

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Over-the-Horizon Radar (OTHR) exploits the refraction of high frequency radiation through the ionosphere layers to detect targets beyond the line-of-sight horizon. Multipath propagation between the radar and the detected targets may results in multiple spatially separated tracks for a single target to be observed at the receiver site. Consequently there is a heavy traffic, especially in case of multiple targets, to be associated and combined if there are tracks represent the same target. In this study, a new method for multipath clustering for OTHR is proposed. The proposed method describes the similarities between all tracks as fuzzy degrees of membership. This method can operate in real-time and can perform clustering and fusion of OTHR tracks with tracks from other sources such as targets reporting global positioning systems and microwave radars. The proposed method has the advantages of less computations and high efficiency compared to conventional fuzzy logic clustering techniques. It has also the advantage of treating all the tracks data at once rather than pairwise. The efficiency of the proposed method is demonstrated using simulated examples.

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Section: Performance Evaluation and Comparisonmentioning

confidence: 99%

Section: Performance Evaluation and Comparisonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A New Method for Multipath Clustering for Over-the-Horizon Radar

Aziz¹,

Abdelrahman²,

Abouelatta³

2016

American Journal of Applied Sciences

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“…For power calculations, it is assumed that there is a load of 1 ohm. If we compare each pair of the result when the target is located at (20,20), Figures 2-4 show that the ML method compresses the distribution of LS estimates more densely around the true value. Some of ML iterative estimates have relatively larger errors.…”

Section: Performance Of Initial Localizationmentioning

confidence: 99%

“…In the simulations, a number of different locations of the targets are estimated. The source targets are located at (20,20), (130, 10), (140, 140), (20,150), and (200, 200), respectively. The number of performed simulations is 1000, and background noise is chosen by three different values (0.01, 0.1, and 0.2 [dB]).…”

Section: Performance Of Initial Localizationmentioning

confidence: 99%

Multitarget Tracking by Particle Filtering Based on RSS Measurement in Wireless Sensor Networks

Lim

Chong

2015

International Journal of Distributed Sensor Networks

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We propose an algorithm for multitarget tracking by particle filtering in wireless sensor networks based on received signal strength (RSS) measurement where we also localize a newly appearing target whose location and reference power are unknown. Therefore, the number, the reference power, and the initial locations of targets are unknown in this problem. At the initial localization step, we apply approximate least squares (LS) method to roughly estimate the target location. After the initial location is estimated, we estimate the reference power. This is possible because we can use multiple number of measurements for estimating multiparameters. The proposed approach is particularly emphasized on the initialization step that completes the whole multitarget tracking system by particle filtering in a challenging scenario. The proposed approach is validated by computer simulations for its effectiveness.

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References

2016

Radar Data Processing With Applications

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A new nearest-neighbor association approach based on fuzzy clustering

Cited by 34 publications

References 37 publications

A New Method for Multipath Clustering for Over-the-Horizon Radar

A New Method for Multipath Clustering for Over-the-Horizon Radar

Multitarget Tracking by Particle Filtering Based on RSS Measurement in Wireless Sensor Networks

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