Dim target detection using high order correlation method

Liou, Ren-Jean; Azimi-Sadjadi, M.R.

doi:10.1109/7.220935

Cited by 48 publications

(27 citation statements)

References 15 publications

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“…(4) Higher-order correlation A method referred to as high order correlation (HOC) was developed which does not make any a priori assumption about the targets and background clutter [170]. In [171], a track scoring mechanism is proposed and a new method is developed to perform data association and track identification in the presence of heavy clutter using the modified HOC.…”

Section: ) 3-d Matched Filtersmentioning

confidence: 99%

A Survey of Motion-Based Multitarget Tracking Methods

Qiu¹,

Zhang²,

Lü³

et al. 2015

PIER B

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Abstract-Multitarget tracking (MTT) in surveillance system is extremely challenging, due to uncertain data association, maneuverable target motion, dense clutter disturbance, and real-time processing requirements. A good many methods have been proposed to cope with these challenges. However, no up-to-date survey is available in the literature that can help to select suitable tracking algorithm for practical problem. This paper provides a comprehensive review of the state-of-the-art motion-based MTT techniques, classifies existing methods into two groups, i.e., the detect-beforetrack (DBT) scheme and the track-before-detect (TBD) scheme. The DBT scheme is employed to achieve robust and tractable tracking performance when the signal-noise-ratio (SNR) is strong. The TBD scheme is used in the scenarios of low SNR, and it aims to cumulate target energy by multiple sensor frames. Furthermore, depending on the data association mechanism, the DBT methods can be classified into two categories, data association based approaches and finite set statistics (FISST) based approaches. And the TBD methods can be classified into non-Bayesian approaches and Bayesian approaches depending on the basis theory used for tracking. For each category, this paper provides the detailed descriptions of the representative algorithms, and examines their pros and cons. Finally, new trends for future research directions are offered.

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Section: ) 3-d Matched Filtersmentioning

confidence: 99%

A Survey of Motion-Based Multitarget Tracking Methods

Qiu¹,

Zhang²,

Lü³

et al. 2015

PIER B

View full text Add to dashboard Cite

show abstract

“…Embedded in the structure of the HOC computation is the curvature and angle description of each segment [2]. The three pixels, one from each consecutive scan line, used for computing a terrn of the HOC equation, define a pair of line segments.…”

Section: Corner Selection Processmentioning

confidence: 99%

“…To identify a correlated pixel set, the spatial correlations among the points on three consecutive scan lines are formed and the consistency in generating correlations in subsequent scans is determined. The process can be described by the following recursive equation [2]: (…”

Section: Fiber Analysis Using High Order Correla Tl Onmentioning

confidence: 99%

See 1 more Smart Citation

Identification and Measurement of Fiber Glass Particles in Electron Microscopy Using a High Order Correlation Process

Yáñez-Suárez

Azimi-Sadjadi

1997

Review of Progress in Quantitative Nondestructive Evaluation

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“…In this paper, a preprocessing scheme based on multichannel subband adaptive filtering and a postprocessing scheme based on the high-order correlation (HOC) method [24], [25] was proposed to improve the SRR before and after the beamforming process. Both schemes were designed to overcome the shortcomings of the existing methods while combining their advantages.…”

mentioning

confidence: 99%

Underwater target detection using multichannel subband adaptive filtering and high-order correlation schemes

Yuan

Azimi-Sadjadi²,

Wilbur³

et al. 2000

IEEE J. Oceanic Eng.

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Abstract-In this paper, new pre-and post-processing schemes are developed to process shallow-water sonar data to improve the accuracy of target detection. A multichannel subband adaptive filtering is applied to preprocess the data in order to isolate the potential target returns from the acoustic backscattered signals and improve the signal-to-reverberation ratio. This is done by estimating the time delays associated with the reflections in different subbands. The preprocessed results are then beamformed to generate an image for each ping of the sonar. The testing results on both the simulated and real data revealed the efficiency of this scheme in time-delay estimation and its capability in removing most of the competing reverberations and noise. To improve detection rate while significantly minimizing the incident of false detections, a high-order correlation (HOC) method for postprocessing the beamformed images is then developed. This method determines the consistency in occurrence of the target returns in several consecutive pings. The application of the HOC process to the real beamformed sonar data showed the ability of this method for removing the clutter and at the same time boosting the target returns in several consecutive pings. The algorithm is simple, fast, and easy to implement.

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Dim target detection using high order correlation method

Cited by 48 publications

References 15 publications

A Survey of Motion-Based Multitarget Tracking Methods

A Survey of Motion-Based Multitarget Tracking Methods

Identification and Measurement of Fiber Glass Particles in Electron Microscopy Using a High Order Correlation Process

Underwater target detection using multichannel subband adaptive filtering and high-order correlation schemes

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