• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.7
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• pp.719-729
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• 1992

An improved MXTM (maximum trimmed mean) -CFAR (constant false alarm rate) processor is proposed to reduce false alarm rates In detecting radar targets and Its performance character is ticsare analyzed to be compared with those of other CFAR processors. The proposed MXTM-CFAR processor is obtained by combining the GO (greatest of ) -CFAR processor reducing excessive falsealarm rate at riutter edges with the TM-CFAR processor showing good performances In homo-geneous Jnonhornog eneous background. Performance analyses have been done by computing detection probability, constant false alarm rate and detection thresholds under the homogeneous or multiple target environments and at the clutter edges. Analysis results how that the proposed CFAR processor maintains its performance as good as those of,05(order statistics) and TM-CFAR inhomogeneous and multiple target environments and Can reduce the false alarm rate at clutter edges. Overall computing time hfs been also reduced.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7C
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• pp.725-734
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• 2006

As a sequel to Part 1, the performance characteristics of the cell averaging (CA), greatest of (GO), and smallest of (SO) constant false alarm rate (CFAR) processors in nonhomogeneous environment are obtained and compared when receiving antenna diversity is employed in the pseudonoise (PN) code acquisition of direct-sequence code division multiple access (DS/CDMA) systems. Unlike in homogeneous environment, the GO CFAR processor is observed to exhibit the best performance in nonhomogeneous environment, with the CA CFAR processor performing the second best.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.1
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• pp.100-105
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• 2011

Generally, because received signals from radar are very bulky, the data are divided into manageable size called section, and sections are distributed into several digital signal processors. And then, target detection algorithms are applied simultaneously in each processor. CFAR(Constant False Alarm Rate) algorithm, which is the most popular target detection algorithm, can estimate accurate threshold values to determine which signals are targets or noises within center-cut of section allocated to each processor. However, its estimation precision is diminished in section edge data because of insufficient surrounding data to be referred. Especially this edge problem of CFAR is too serious if we have many sections to be processed, because it causes many false alarms in most every section edges. This paper describes false alarm issues on MCA(Minimum Cell Average)-CFAR, and proposes a false alarm elimination method by changing section size alternatively. Real received data from multi-function radar were used to evaluate a proposed method, and we show that our method drastically decreases false alarms without missing real targets, and improves detection performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.371-380
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• 2006

The performance characteristics of the cell averaging(CA), greatest of(GO), and smallest of(SO) constant false alarm rate(CFAR) processors in homogeneous environment are obtained and compared when receiving antenna diversity is employed in the pseudonoise code acquisition of direct-sequence code division multiple access (DS/CDMA) systems. From the simulation results, it is observed that the CA CFAR scheme has the best performance and the GO CFAR scheme has almost the same performance as the CA CFAR scheme in homogeneous environment. In Part 2 of this paper, the CA, GO, and SO CFAR processors for code acquisition in nonhomogeneous environment are addressed.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1991.10a
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• pp.92-95
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• 1991

Constant false alarm rate(CFAR) processors are useful for detecting radar targets in background for which all parameters in the statistical distribution are not known and may be nonstationary. The well known "cell averging" (CA) CFAR processor is known to yield best performance in homogeneous case, but exhibits severe performance in the presence of an interfering target in the reference window or/and in the region of clutter edges. The "order statistics"(OS) CFAR processor is known to have a good performance above two nonhomogeneous cases. The modified OS-CFAR processor, known as "trimmed mean"(TM) CFAR processor performs somewhat better than the OS-CFAR processor by judiciously trimming the ordered samples. This paper proposes and analyzes the performance of a new CFAR processor called the "maximum trimmed mean"(MX-TM) CFAR processor combining the "greatest of"(GO) CFAR and TM-CFAR processors. The MAX operation is included to control false alarms at clutter edges. Our analyses show that the proposed CFAR processor has similar performance TM- and OS-CFAR processors in homogeneous case and in the precence of interfering targets, but can control the false rate in clutter edges. Simulation results are presented to demonstrate the qualitative effects of various CFAR processors in nonhomogeneous clutter environments.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.2
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• pp.227-236
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• 2001

This paper proposes a frequency-domain partially adaptive algorithm, called a censoring algorithm, to reduce the computational complexity of the frequency domain adaptive array. The proposed censoring algorithm determines the existence of interferences in the frequency-domain at each frequency bin using a constant false alarm rate (CFAR) processor. The censoring algorithm adapts only those parts of the weights that correspond to the frequency bins expected to contain interferences. The censoring algorithm is also expanded to overcome the signal cancellation phenomenon caused by smart jammers. Accordingly, a censoring spatial smoothing, which combines the censoring algorithm with spatial smoothing, is proposed. Simulation results show that the proposed algorithms are effective in removing interferences with only part of the computational complexity of conventional algorithms yet with the same level of performance.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.2
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• pp.69-80
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• 2002

In this paper, signed-rank based nonparametric detectors are used for direct sequence code division multiple access pseudo-noise code acquisition systems in frequency-selective Rician fading channels. We first derive the locally optimum rank detector, and then propose the locally suboptimum rank (LSR) and k-th order modified signed-rank (MSRk) detectors using approximate score functions. We compare the serial and hybrid parallel double-dwell schemes using the LSR and MSRk detectors with those using the conventional squared-sum (SS) using the cell averaging constant false alarm rate processor and modified sign detectors. From the simulation results, it is shown that the LSR and MSRk detectors perform better than the SS detector using the cell averaging constant false alarm rate processor.

• Proceedings of the Acoustical Society of Korea Conference
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• 1991.06a
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• pp.163-168
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• 1991

In this paper, we propose a new systolic architecture for the order statistics(OS) constant false alarm rate(CFAR) processor. In the proposed architecture, each processing element(PE) can compare two reference data cells with one test cell simultaneously in each clock cycle. So the utilization of each PE in this architecture is 100% whereas the utilization of each PE in the systolic architecture previously reported by Ritcey and Hwang is 50% because of one clock delay between two adjacent PE's active in computation. This can speed up the data processing rate by a factor of two. With this architecture, we can obtain the reduced number of communication links between adjacent PE's and reduction of the latency by half in comparison with the one proposed by Ritcey and Hwang.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.4
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• pp.482-490
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• 2017

The radar signal processing procedure is divided into the pre-processing such as frequency down converting, down sampling, pulse compression, and etc, and the post-processing such as doppler filtering, extracting target information, detecting, tracking, and etc. The former is generally designed using FPGA because the procedure is relatively simple even though there are large amounts of ADC data to organize very quickly. On the other hand, in general, the latter is parallel processed by multiple DSPs because of complexity, flexibility and real-time processing. This paper presents the radar signal processor design using FPGA which includes not only the pre-processing but also the post-processing such as doppler filtering, bore-sight error, NCI(Non-Coherent Integration), CFAR(Constant False Alarm Rate) and etc.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.3
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• pp.37-46
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• 2012

In RADAR and SONAR detection systems, noise environment can be classified into homogeneous and heterogeneous environment. Especially heterogeneous environments are modelled as target masking and clutter edge. Since the variability-index (VI) CFAR, a composed CFAR algorithm, dynamically selects one of the mean-level algorithms based on the VI and the MR (mean ratio) test, it is robust to various environments. However, the VI CFAR still suffers from lowered detection probabilities in heterogeneous environments. To overcome these problems, we propose an improved VI CFAR processor where TM (trimmed mean) CFAR and a sub-windowing technique are introduced to minimize the degradation of the detection probabilities appeared in heterogeneous environments. Computer simulation results show that the proposed method has the better performance in terms of detection probability and false alarm probability compared to the VI CFAR and single CFAR algorithms.