New algorithm for multi targets detection in clutter edge radar environments

Kamal, Mustafa Subhi; Abdullah, Jiwa

doi:10.11591/ijeecs.v18.i1.pp420-427

Cited by 3 publications

(4 citation statements)

References 8 publications

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“…It is proved that the transformed data by the G α,β group also have a Gumbel distribution. Furthermore, the statistics of the transformed data G α,β (W ) are mentioned in Equations ( 7) and (8):…”

Section: Log-t-cfarmentioning

confidence: 99%

“…In the literature, various types of CFAR detectors have been suggested, each of which is appropriate for a certain operating environment [2][3][4]. Since the detection environment is generally nonhomogeneous and cannot contain all reference cells Independent and Identically Distributed (IID), a reference window may contain clutter-edges and multiple targets, which are the main causes of the heterogeneity of the environment [4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Enhancing Detection Performances of Nonhomogeneous Weibull Clutter by Knowledge Based Systems Exploitation

Rouabah¹,

Hamadouche²,

Teguig³

et al. 2021

PIER B

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This article aims to study the behavior of Constant False Alarm Rate (CFAR) detectors for a heterogeneous Weibull clutter and its derivatives. CFAR architectures based on exploitation of the Combined Environmental Knowledge Base (CEKB) have been proposed, called Knowledge Based Systems-Maximum Likelihood-CFAR (KBS-ML-CFAR) and KBS-Log-t-CFAR for nonhomogeneous Weibull clutter at general parameters. A CFAR architecture that uses Geographic Information System (GIS) as a Knowledge Base (KB), called KBS-Forward Automatic Order Selection Ordered Statistics-CFAR (KBS-FAOSOS-CFAR) has been proposed for special Weibull parameters. The performances of the proposed detectors have been studied and analyzed by conducting MATLAB simulations. The simulation results show that the KBS-CFAR based on CEKB outperforms the ML and Log-t-CFAR in terms of clutter edge detection capability in nonhomogeneous Weibull clutter case. Compared with other KB, this KBS-CFAR based on CEKB performs well to preserve the probability of false alarm (P f a ) at a desired constant value. For special Weibull parameters, the proposed KBS-FAOSOS-CFAR based on GIS performs better than KBS-Dynamic-CFAR and KBS-Adaptive Linear Combined-CFAR (KBS-ALC-CFAR) in severe interference case. CFAR techniques have been implemented on the ADSP (Advanced Digital Signal Processor) processing board, and the results have been evaluated and discussed.

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Section: Log-t-cfarmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Enhancing Detection Performances of Nonhomogeneous Weibull Clutter by Knowledge Based Systems Exploitation

Rouabah¹,

Hamadouche²,

Teguig³

et al. 2021

PIER B

View full text Add to dashboard Cite

show abstract

“…Along with the development of multi-antenna systems on radar technology that detects multiple targets at a long distance, it has a detection function and a flexible response to the target state and its surroundings, supported by high detection accuracy and angle resolution. One of the most important factors in radar performance is optimal range and tracking angle [1] and multi-target detection [2]. High accuracy enhances the ability to detect targets, and high angle resolution increases the number of detected targets.…”

Section: Introductionmentioning

confidence: 99%

Subarrays of phased-array antennas for multiple-input multiple-output radar applications

Tahcfulloh

Hardiwansyah²

2022

IJ-ICT

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The subarray MIMO radar (SMIMO) is a multiple-input multiple-output (MIMO) radar with elements in the form of a sub-array that acts as a phased array (PAR), so it combines at the same time the key advantage of the PAR radar, which is high directional gain to increase target range, and the key advantage of the MIMO radar, i.e., high diversity gains to increase the maximum number of detected targets. Different schemes for the number of antenna elements in the transceiver zones, such as uniform and/or variable, overlapped and non-overlapped, significantly determine the performance of radars as virtual arrays (VARs), maximum number of detected targets, accuracy of target angle, detection resolution, SNR detection, and detection probability. Performance is also compared with the PAR, the MIMO, and the phased MIMO radars (PMIMO). The SMIMO radar offers great versatility for radar applications, being able to adapt to different shapes of the multiple targets to be detected and their environment. For example, for a transmit-receive with an antenna element number, i.e., M = N = 8, the range of the number of detected targets for the SMIMO radar is flexible compared to the other radars. On the other hand, the proposed radar's signal-to-noise ratio (SNR) detection performance and detection probability (K = 5, L = 3) are both 1,999 and above 90%, which are better than other radars.

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“…Thus, the MIMO configuration with multifrequency was proposed to be adopted for maritime target's estimation. Similar to all radar applications, the proposed configuration works based on the concept of signal reflection by a target of interest [9]- [12]. However, implementing the signal over MIMO requires orthogonality between FMCW signals as presented by Hinz et al in their paper [13] , which discussed the advantages and disadvantages of each FMCW MIMO approach.…”

Section: Introductionmentioning

confidence: 99%

A small vessel detection using a co-located multi-frequency FMCW MIMO radar

Zainuddin

Rashid

Pasya

et al. 2021

IJECE

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Small vessels detection is a known issue due to its low radar cross section (RCS). An existing shore-based vessel tracking radar is for long-distance commercial vessels detection. Meanwhile, a vessel-mounted radar system known for its reliability has a limitation due to its single radar coverage. The paper presented a co-located frequency modulated continuous waveform (FMCW) maritime radar for small vessel detection utilising a multiple-input multiple-output (MIMO) configuration. The radar behaviour is numerically simulated for detecting a Swerling 1 target which resembles small maritime’s vessels. The simulated MIMO configuration comprised two transmitting and receiving nodes. The proposal is to utilize a multi-frequency FMCW MIMO configuration in a maritime environment by applying the spectrum averaging (SA) to fuse MIMO received signals for range and velocity estimation. The analysis was summarised and displayed in terms of estimation error performance, probability of error and average error. The simulation outcomes an improvement of 2.2 dB for a static target, and 0.1 dB for a moving target, in resulting the 20% probability of range error with the MIMO setup. A moving vessel's effect was observed to degrade the range error estimation performance between 0.6 to 2.7 dB. Meanwhile, the proposed method was proven to improve the 20% probability of velocity error by 1.75 dB. The impact of multi-frequency MIMO was also observed to produce better average error performance.

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New algorithm for multi targets detection in clutter edge radar environments

Cited by 3 publications

References 8 publications

Enhancing Detection Performances of Nonhomogeneous Weibull Clutter by Knowledge Based Systems Exploitation

Enhancing Detection Performances of Nonhomogeneous Weibull Clutter by Knowledge Based Systems Exploitation

Subarrays of phased-array antennas for multiple-input multiple-output radar applications

A small vessel detection using a co-located multi-frequency FMCW MIMO radar

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