CA-CFAR Detection Performance in Homogeneous Weibull Clutter

García, Fernando Darío Almeida; Rodriguez, Andrea Carolina Flores; Fraidenraich, Gustavo; Filho, José Cândido Silveira Santos

doi:10.1109/lgrs.2018.2885451

Cited by 56 publications

(23 citation statements)

References 18 publications

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“…Therefore, we introduce the pixel distribution of reverberation noise into the adaptive threshold solution. According to the definition of false alarm rate in equation ( 2), when a constant false alarm rate is set, the relationship between false alarm rate and detection threshold will be obtained, as shown in equation ( 5) [20]:…”

Section: D-weibull-ca-cfarmentioning

confidence: 99%

Track Detection of Underwater Moving Targets Based on CFAR

Zhang

Mao

Ouyang

et al. 2023

J. Phys.: Conf. Ser.

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In this paper, we propose a 2D-Weibull-Constant False Alarm Rate (2D-Weibull-CFAR) detection algorithm to solve the problem that detecting current underwater targets is difficult due to the influence of reverberation noise. Specifically, referring to the idea that CFAR uses the probability distribution of reference units to detect objects, this paper introduces the pixel distribution of reverberation noise into the CFAR detector. After that, the probability distribution of the extracted reference units is estimated, and then the adaptive detection threshold is obtained to achieve reliable detection of underwater targets. Finally, the Hough transform extracts the trajectory of the detection results. The experimental test shows that the algorithm in this paper can solve the problem of false alarms and missed alarms in detecting targets hidden in the reverberation noise. The algorithm in this paper can effectively detect the target in the reverberation noise. The detection results show that the algorithm in this paper has higher accuracy and lower false alarm rate than the comparison algorithm.

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Section: D-weibull-ca-cfarmentioning

confidence: 99%

Track Detection of Underwater Moving Targets Based on CFAR

Zhang

Mao

Ouyang

et al. 2023

J. Phys.: Conf. Ser.

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“…CFAR detection is a general adaptive algorithm in radar fields to detect the target returns against background noises and clutters in [18]. In particular, Cell Averaging CFAR (CA-CFAR) in [19] is applied to the static clutter reduced signals expressed in (2).…”

Section: Multi-target Tracking Algorithmmentioning

confidence: 99%

“…The a-posteriori pdf of target track state, p{xk τ | χk τ , Zk} is calculated by the KF estimator, KFE, based on the validated measurement in (19). Each track state estimate and its covariance are merged by using the data association probability as the weighting coefficient in (20) and (21)…”

Section: B Multiple Target Tracking Stepmentioning

confidence: 99%

Multiple Sensor Linear Multi-Target Integrated Probabilistic Data Association for Ultra-Wide Band Radar

Shin

Son

2020

IEEE Access

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Ultra-Wide Band (UWB) radar has a number of advantages of resolving multipath, exceptional spatial resolution, and ranging performance. However, several difficulties are confronted for multiple target tracking using UWB radars such as clutter signals which contaminate target signals, and unidentified number and behavior of the targets. Hence, this paper presents to develop a multiple moving target tracking algorithm, consisting of preprocessing and multiple target tracking steps. In the preprocessing step, static clutter reduction and constant false alarm rate (CFAR) detection extract the target candidate range measurements from each UWB radar. Then, two multiple target tracking (MTT) steps are developed: range-based MTT and position-based MTT. The range-based MTT is mainly based on existing linear multi-target integrated probabilistic data association (LM-IPDA) from each UWB radar measurement. Then the outputs of each LM-IPDA are gathered in the positioning center to estimate the position of multiple targets. On the other hands, the position-based MTT is based on multiple sensor LM-IPDA (msLM-IPDA) as an accurate target tracking method for various uncertainties by improving the probabilistic model of LM-IPDA. The tracking performance of two MTT methods is investigated with both numerical simulation and experiments.

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“…A novel and exact formulation for the probability of detection of a cell‐averaging and CFAR radar system operating in a homogeneous clutter environment are presented in Ref. [31]. Novel linear and non‐linear detectors are proposed with diversified robust or selective behaviours to analyse and design the outperforming radar detectors [32].…”

Section: Introductionmentioning

confidence: 99%

The improved constant false alarm rate detector based on multi‐frame integration for fluctuating target detection in heavy‐tailed clutter

Cao

Zhao

2023

IET Signal Processing

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In this paper, attention is devoted to the analysis of the detection threshold based on the multi-frame integration in heavy-tailed clutter for the radar with high resolution and even smaller grazing angle. The closed-form expressions of both the probability of the detection and the probability of false alarm for the heavy-tailed clutter background, which can be used for the theoretical analysis of constant false alarm rate (CFAR) detectors, are derived with the multi-frame integration technique. Accordingly, an improved CFAR detector is designed to work well with the presence of target-like outliers in the heavytailed clutter. In addition, the proposed CFAR detector is capable to alleviate the masking-effect resorting to the additive feedback operation when a target is large enough to cross several cells in multi-target case. The theoretical analysis and numerical simulations demonstrate that the proposed CFAR detector based on multi-frame integration can improve the signal-to-clutter rate of the targets exhibiting better performance than ones based on single frame in heavy-tailed clutter background. It is validated from the simulations that the proposed CFAR detector with additive feedback operation can deal with masking-effect for large target occupying several cells.

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CA-CFAR Detection Performance in Homogeneous Weibull Clutter

Cited by 56 publications

References 18 publications

Track Detection of Underwater Moving Targets Based on CFAR

Track Detection of Underwater Moving Targets Based on CFAR

Multiple Sensor Linear Multi-Target Integrated Probabilistic Data Association for Ultra-Wide Band Radar

The improved constant false alarm rate detector based on multi‐frame integration for fluctuating target detection in heavy‐tailed clutter

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