The effect of windowing on the performance of the CA-CFAR and OS-CFAR algorithms

Melebari, Asem; Melebari, Amer; Alomar, Waleed A.; Gaffar, Mohammed Yunus Abdul; Wind, R. De; Cilliers, J.E.

doi:10.1109/radarconf.2015.7411889

Cited by 5 publications

(7 citation statements)

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“…In the CA-CFAR detector, the estimation of the background clutter power level is the average of

reference units, which is the maximum likelihood estimation of the clutter power level given that the reference units samples obeys the exponential distribution [ 23 , 24 ]. Define:

where, Z is the total clutter power level estimation.…”

Section: Adaptive Radiation Power Of Airborne Jammermentioning

confidence: 99%

“…The false alarm probability detected by CA-CFAR will increase at the clutter edge, and if the radar signal appear in the sliding window, the detection performance of the detector will be reduced. As a modification scheme of CA-CFAR, the maximum value selection of CFAR detection and the minimum value selection CFAR are proposed [ 23 , 24 , 25 ]. When the interference source only exists in the front sliding window or the rear sliding window, SO-CFAR is better to detect multiple radar signals, but its false alarm capability is poor.…”

Section: Adaptive Radiation Power Of Airborne Jammermentioning

confidence: 99%

“…GO-CFAR can maintain a stable false alarm probability in the clutter edge environment, but the detection performance in a multiple radar signals environment is worse. GO-CFAR is mainly used for clutter edges, which takes advantage of the maximum local estimation as the total clutter power level of the detector, that is [ 23 , 24 ]:

…”

Section: Adaptive Radiation Power Of Airborne Jammermentioning

confidence: 99%

“…However, CA-CFAR was analyzed in the Rayleigh clutter background and found that its detection performance was greatly influenced by the clutter characteristics. In order to reduce the impact of clutter in the tracking target process, a unit average maximum detector (Greatest of Constant False Alarm Rate, GO-CFAR) and a unit average selection detector (Smallest of Constant False, SO-CFAR)have been proposed [ 23 , 24 , 25 ]. To further improve the detection performance, luo (2009) and liu (2001) proposed a new CFAR detection algorithm which can not only process time domain data in, but also convert the data into frequency domain and wavelet domain for further processing [ 26 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

“…And results show that GO-CFAR can maintain a stable false alarm probability at the edge of the clutter, but the detection performance of GO-CFAR decreases in multi-target scenarios. On the contrary, SO-CFAR maintains good detection performance in multiple targets situations, but the false alarm capability at the edge of the clutter is seriously affected.The detection performance of OS-CFAR is between GO-CFAR and SO-CFAR [ 23 , 24 , 25 ]. An (2015) proposed a constant false alarm detection method based on summation.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Target Tracking While Jamming by Airborne Radar for Low Probability of Detection

Wang

Cong

Shi

et al. 2018

Sensors

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Although radiation power minimization is the most important method for an advanced stealth aircraft to achieve the low probability of detection (LPD) performance against the opposite passive detection system (PDS), it is not always effective when the performance of PDS is advanced. In a target tracking scenario, an interference tactic is proposed in this paper to keep the airborne radar in an LPD state. Firstly, this paper introduces the minimization radiation power design of airborne radar based on the distance between the radar and the target, and introduces the minimization radiation power design of the airborne jammer based on the predicted detection probability of the opposite PDS. Then, after consulting the most commonly used constant false alarm rate (CFAR) technologies in passive detection systems, including the cell average CFAR, the greatest of CFAR, the smallest of CFAR and the ordered statistic CFAR, this paper analyzes their relationships and points out the way of interference. Finally, based on the constraints, not only including the predicted detection probabilities of airborne radar and opposite PDS, respectively, but also including the time synchronization which is necessary to avoid the leaked interference power generated by airborne jammer jamming the airborne radar echoes from the target, this paper establishes a math model to minimize the total interference power of airborne jammer without interfering target tracking. Simulation results show that the proposed model is effective.

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“…In the CA-CFAR detector, the estimation of the background clutter power level is the average of

reference units, which is the maximum likelihood estimation of the clutter power level given that the reference units samples obeys the exponential distribution [ 23 , 24 ]. Define:

where, Z is the total clutter power level estimation.…”

Section: Adaptive Radiation Power Of Airborne Jammermentioning

confidence: 99%

Section: Adaptive Radiation Power Of Airborne Jammermentioning

confidence: 99%