Fuzzy-based MTD

2020 ◽  
Vol 54 (1) ◽  
pp. 66-84
Author(s):  
Eppili Jaya ◽  
B.T. Krishna
Keyword(s):  
Design Methodology ◽  
Moving Objects ◽  
Target Location ◽  
Fractional Fourier Transform ◽  
Search Space ◽  
Moving Target ◽  
Content Type ◽  
Linguistic Rules ◽  
Peak Energy ◽  
Fuzzy Linguistic

Purpose Synthetic aperture radar exploits the receiving signals in the antenna for detecting the moving targets and estimates the motion parameters of the moving objects. The limitation of the existing methods is regarding the poor power density such that those received signals are essentially to be transformed to the background ratio. To overcome this issue, fractional Fourier transform (FrFT) is employed in the moving target detection (MTD) process. The paper aims to discuss this issue. Design/methodology/approach The proposed MTD method uses the fuzzy decisive approach for detecting the moving target in the search space. The received signal and the FrFT of the received signal are subjected to the calculation of correlation using the ambiguity function. Based on the correlation, the location of the target is identified in the search space and is fed to the fuzzy decisive module, which detects the target location using the fuzzy linguistic rules. Findings The simulation is performed, and the analysis is carried out based on the metrics, like detection time, missed target rate, and MSE. From the analysis, it can be shown that the proposed Fuzzy-based MTD process detected the object in 5.0237 secs with a minimum missed target rate of 0.1210 and MSE of 23377.48. Originality/value The proposed Fuzzy-MTD is the application of the fuzzy rules for locating the moving target in search space based on the peak energy of the original received signal and FrFT of the original received signal.

A Particle Fuzzy Decisive Framework for Moving Target Detection in the Multichannel SAR Framework

2020 ◽  
Vol 19 (04) ◽  
pp. 2050032
Author(s):  
Eppili Jaya ◽  
B. T. Krishna
Keyword(s):  
Fourier Transform ◽  
Target Detection ◽  
Fuzzy System ◽  
Target Location ◽  
Fractional Fourier Transform ◽  
Moving Target ◽  
Detection Time ◽  
Moving Target Detection ◽  
Genetic Fuzzy System ◽  
Linguistic Rules

Target detection is one of the important subfields in the research of Synthetic Aperture Radar (SAR). It faces several challenges, due to the stationary objects, leading to the presence of scatter signal. Many researchers have succeeded on target detection, and this work introduces an approach for moving target detection in SAR. The newly developed scheme named Adaptive Particle Fuzzy System for Moving Target Detection (APFS-MTD) as the scheme utilizes the particle swarm optimization (PSO), adaptive, and fuzzy linguistic rules in APFS for identifying the target location. Initially, the received signals from the SAR are fed through the Generalized Radon-Fourier Transform (GRFT), Fractional Fourier Transform (FrFT), and matched filter to calculate the correlation using Ambiguity Function (AF). Then, the location of target is identified in the search space and is forwarded to the proposed APFS. The proposed APFS is the modification of standard Adaptive genetic fuzzy system using PSO. The performance of the MTD based on APFS is evaluated based on detection time, missed target rate, and Mean Square Error (MSE). The developed method achieves the minimal detection time of 4.13[Formula: see text]s, minimal MSE of 677.19, and the minimal moving target rate of 0.145, respectively.

scholarly journals Moving Target Detection in Multichannel SAR Framework using Adaptive Neuro Fuzzy Decisive Technique

2019 ◽  
Vol 8 (2) ◽  
pp. 4517-4523 ◽  
Keyword(s):  
Target Detection ◽  
Target Location ◽  
Fractional Fourier Transform ◽  
Research Area ◽  
Moving Target ◽  
Moving Targets ◽  
Moving Target Detection ◽  
Neuro Fuzzy ◽  
Linguistic Rules ◽  
Background Clutter

Precise and efficacious detection of moving targets is a prominent task in on-going synthetic aperture radar (SAR) technique. The perception of moving object allows quite significant data about the situation under observation for both surveillance and intelligence activities. The task of accurately locating moving targets against strong background clutter in minimum of time is of utmost interest in the current research area. Fractional Fourier Transform (FrFT) concentrates the energy of the required chirp signal so that it can be well separated from the chirp like noise. The proposed SAR Moving Target Detection (MTD) process is based on the combination of FrFT with the adaptive-neuro fuzzy decisive technique. The correlation among the received signal and the FrFT of the received signal are computed which maximizes the required signal energy and applied to the adaptive-neuro fuzzy decisive module that detects the target location adaptively using the fuzzy linguistic rules. The simulation is performed by changing the number of targets, different Pulse repetition intervals, antenna turn velocity, iterations and the analysis is carried out based on the metrics, like detection time, missed target rate, and Mean Square Error (MSE), proving that the proposed Adaptive-Neuro Fuzzy-based MTD process detected the object in 5.0237 secs with a minimum missed target rate of 0.1210 and MSE of 23377.48.

Stochastic portfolio optimization using efficiency evaluation

2015 ◽  
Vol 53 (8) ◽  
pp. 1698-1713 ◽  
Author(s):  
Paulo Rotela Junior ◽  
Edson de Oliveira Pamplona ◽  
Luiz Célio Souza Rocha ◽  
Victor Eduardo de Mello Valerio ◽  
Anderson Paulo Paiva
Keyword(s):  
Design Methodology ◽  
Stock Exchange ◽  
Search Space ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Risk And Uncertainty ◽  
Content Type ◽  
Support Tool ◽  
Stock Investment ◽  
Risk Criterion

Purpose – The purpose of this paper is to analyze portfolios chosen using an efficiency evaluation that considers risk and uncertainty and optimizes the allocation of invested capital using the Sharpe approach. Design/methodology/approach – The portfolios comprised shares on the Sao Paulo Stock Exchange. A chance-constrained data envelopment analysis stochastic optimization model was used, and return and variance were employed as input and output variables. Findings – The model was shown to be viable. It reduced the search space and considered data randomness. Originality/value – Three portfolios were proposed. The variation of the model’s risk criterion fulfilled the requirements of investors with different attitudes to risk. The model proposed can be used as a support tool for stock investment decisions.

scholarly journals Innovative Multi-Target Estimating with Clutter-Suppression Technique for Pulsed Radar Systems

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2446
Author(s):  
Jo-Yen Nieh ◽  
Yuan-Pin Cheng
Keyword(s):  
Doppler Shift ◽  
Moving Objects ◽  
Target Location ◽  
Moving Target ◽  
Detection Range ◽  
Radar Systems ◽  
Suppression Technique ◽  
Efficient Scheme ◽  
Detection Energy ◽  
Cluttered Background

Linear frequency modulation (LFM) waveforms have high Doppler-shift endurance because of the relative wide modulation bandwidth to the Doppler variation. The Doppler shift of the moving objects, nevertheless, constantly introduces obscure detection range offsets despite the exceptional Doppler tolerance in detection energy loss from LFM. An up-down-chirped LFM waveform is an efficient scheme to resolve the true target location and velocity by averaging the detection offset of two detection pairs from each single chirp LFM in opposite slopes. However, in multiple velocity-vary-target scenarios, without an efficient grouping scheme to find the detection pair of each moving target, the ambiguous detection results confine the applicability of precise target estimation by using these Doppler-tolerated waveforms. A succinct, three-multi-Doppler-shift-compensation (MDSC) scheme is applied to resolve the range and velocity of two moving objects by sorting the correct LFM detection pair of each target, even though the unresolvable scenarios of two close-by targets imply a fatal disability of detecting objects under a cluttered background. An innovative clutter-suppressed multi-Doppler-shift compensation (CS-MDSC) scheme is introduced in this research to compensate for the critical insufficient of resolving two overlapping objects with different velocities by solely MDSC. The CS-MDSC has been shown to successfully overcome this ambiguous scenario by integrating Doppler-selective moving target indication (MTI) filters to mitigate the distorting of near-zero-Doppler objects.

PSO-based group-oriented crow search algorithm (PGCSA)

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sudeepa Das ◽  
Tirath Prasad Sahu ◽  
Rekh Ram Janghel
Keyword(s):  
Design Methodology ◽  
Search Algorithm ◽  
Search Space ◽  
Benchmark Problems ◽  
Exploration And Exploitation ◽  
Swarm Optimization ◽  
Content Type ◽  
Engineering Problems ◽  
Novel Approaches ◽  
Two Phases

Purpose The purpose of this paper is to modify the crow search algorithm (CSA) to enhance both exploration and exploitation capability by including two novel approaches. The positions of the crows are updated in two approaches based on awareness probability (AP). With AP, the position of a crow is updated by considering its velocity, calculated in a similar fashion to particle swarm optimization (PSO) to enhance the exploiting capability. Without AP, the crows are subdivided into groups by considering their weights, and the crows are updated by conceding leaders of the groups distributed over the search space to enhance the exploring capability. The performance of the proposed PSO-based group-oriented CSA (PGCSA) is realized by exploring the solution of benchmark equations. Further, the proposed PGCSA algorithm is validated over recently published algorithms by solving engineering problems. Design/methodology/approach In this paper, two novel approaches are implemented in two phases of CSA (with and without AP), which have been entitled the PGCSA algorithm to solve engineering benchmark problems. Findings The proposed algorithm is applied with two types of problems such as eight benchmark equations without constraint and six engineering problems. Originality/value The PGCSA algorithm is proposed with superior competence to solve engineering problems. The proposed algorithm is substantiated hypothetically by using a paired t-test.

scholarly journals Visual Sequence Algorithm for Moving Object Tracking and Detection in Images

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Renzheng Xue ◽  
Ming Liu ◽  
Xiaokun Yu
Keyword(s):  
Target Detection ◽  
Difference Method ◽  
Moving Objects ◽  
Target Location ◽  
Mean Shift ◽  
Detection Algorithm ◽  
Moving Target ◽  
Size Change ◽  
Detection And Tracking ◽  
Frame Difference

Objective. The effects of different algorithms on detecting and tracking moving objects in images based on computer vision technology are studied, and the best algorithm scheme is confirmed. Methods. An automatic moving target detection and tracking algorithm based on the improved frame difference method and mean-shift was proposed to test whether the improved algorithm has improved the detection and tracking effect of moving targets. The algorithm improves the traditional three-frame difference method and introduces a single Gaussian background model to participate in target detection. The improved frame difference method is used to detect the target, and the position window and center of the target are determined. Combined with the mean-shift algorithm, it is determined whether the template needs to be updated according to whether it exceeds the set threshold so that the algorithm can automatically track the moving target. Results. The position and size of the search window change as the target location and size change. The Bhattacharyya similarity measure ρ (y) exceeds the threshold r, and the target detection algorithm is successfully restarted. Conclusion. The algorithm for automatic detection and tracking of moving objects based on the improved frame difference method and mean-shift is fast and has high accuracy.

Search for a moving target under minimax estimation

1981 ◽  
Vol 18 (01) ◽  
pp. 167-180 ◽  
Author(s):  
Thomas L. Corwin
Keyword(s):  
Prior Distribution ◽  
Prior Probability ◽  
Target Location ◽  
Search Space ◽  
Moving Target ◽  
Bayes Estimators ◽  
Minimax Estimator ◽  
Starting Position ◽  
Initial Location ◽  
Minimax Estimators

A target is assumed to choose its starting position in a search at an unknown position in a finite search space. No prior probability distribution for the target's initial location is assumed. During the search the target is assumed to move from position to position in the search space according to a Markov process. A search is defined to be the observation of a sequence of random variables. Representations for the minimax estimator for target location at any stage of the search, the least favorable prior distribution for the target, and the value of the estimation game are presented. An example is computed in which Bayes estimators are compared with minimax estimators for target location.

An approach to task recommendation in crowdsourcing based on 2-tuple fuzzy linguistic method

Kybernetes ◽  
2018 ◽  
Vol 47 (8) ◽  
pp. 1623-1641 ◽  
Author(s):  
Xuefeng Zhang ◽  
Jiafu Su
Keyword(s):  
Design Methodology ◽  
Response Rate ◽  
Implementation Process ◽  
Linguistic Terms ◽  
Content Type ◽  
Imprecise Information ◽  
Two Factors ◽  
And Performance ◽  
Fuzzy Linguistic ◽  
Practical Implications

Purpose Task recommendation is an important way for workers and requesters to get better outcomes in shorter time in crowdsourcing. This paper aims to propose an approach based on 2-tuple fuzzy linguistic method to recommend tasks to the workers who would be capable of completing and accept them. Design/methodology/approach In this paper, worker’s capability-to-complete (CTC) and possibility-to-accept (PTA) for a task needs to be recommended are proposed, measured and aggregated to determine worker’s priority for task recommendation. Therein, the similarity between the recommended task and its similar tasks and worker’s performance on these similar tasks are computed and aggregated to determine worker’s CTC quantitatively. In addition, two factors of worker’s active degree and worker’s preferences to a task category are presented to reflect and determine worker’s PTA. In the process of measuring them, 2-tuple fuzzy linguistic method is used to represent, process and aggregate vague and imprecise information. Findings To demonstrate the implementation process and performance of the proposed approach, an illustrative example is conducted on Taskcn, a widely used Chinese online crowdsourcing market. The experimental results show that the proposed approach outperformed the self-selection approach, especially for complex or creative tasks. Moreover, comparing with task recommendation considering worker’s CTC solely, the proposed approach would be better in terms of workers’ response rate. Additionally, the use of linguistic terms and fuzzy linguistic method facilitates the expression of vague and subjective information and makes recommendation process more practical. Research limitations/implications In the study, the authors capture alternative workers, collect workers’ behaviors and compute workers’ CTC and PTA manually. However, as the number of tasks and alternative workers grow, the issue, i.e. how to conveniently collect workers’ behaviors and determine their CTC and PTA, becomes conspicuous and needs to be studied further. Practical implications The proposed approach provides an alternative way to perform tasks posted in crowdsourcing platforms. It can assist workers to contribute to right tasks, and requesters to get outcomes with high quality more efficiently. Originality/value This study proposes an approach to task recommendation in crowdsourcing that integrates workers’ CTC and PTA for the recommended tasks and can deal with vague and imprecise information.

scholarly journals Adaptive Genetic Fuzzy Decisive Technique Based Moving Target Identification using Multichannel SAR Set-up

2019 ◽  
Vol 9 (2S3) ◽  
pp. 168-171
Keyword(s):  
Target Identification ◽  
Synthetic Aperture ◽  
Moving Target ◽  
Chirp Signal ◽  
Signal Energy ◽  
Linguistic Rules ◽  
Transmitted Signal ◽  
Set Up ◽  
Fuzzy Linguistic ◽  
Number Of Iterations

In the ongoing synthetic aperture radar (SAR) methodology, precise and efficient identification of moving targets is a prominent task. Fractional FT (FrFT)accumulates the energy of the required chirp signal in order to separate it as noise from the chirp.The proposed SAR Moving Target Identification (MTI) process is based on FrFT being combined with the definitive adaptive genetic or neurofuzzy method. The correlation between the transmitted signal and the received signal's FrFT is determined, optimizing the appropriate signal energy and applying it to the decisive adaptive genetic fuzzy unit, which identifies the object location using the fuzzy linguistic rules adaptively.The simulation is conducted by changing the number of targets and number of iterations and the evaluation is performed based on parameters such as missed target rate, detection time and Mean Square Error (MSE), showing that the proposed Adaptive Genetic Fuzzy decisiveMTIsystem located the object with a minimum missed target rate of 0.12 in 5.02s and MSE of 23377.4

Linguistic performance and legibility of auditors’ reports with modified opinions

2016 ◽  
Vol 24 (1) ◽  
pp. 105-130 ◽  
Author(s):  
Mondher Fakhfakh
Keyword(s):  
Design Methodology ◽  
Financial Statements ◽  
Structural Features ◽  
International Federation ◽  
Linguistic Features ◽  
Content Type ◽  
Linguistic Performance ◽  
Original Investigation ◽  
Compliance Level ◽  
Linguistic Rules

Purpose – The purpose of this paper is to measure the understandability of the illustrations provided by the International Federation of Accountants in terms of the structural features of international auditors’ reports with modified opinions. Design/methodology/approach – Measurement of the legibility of reports illustrated by the revised ISA 705 and ISA 706. This paper discusses the compliance level of modified auditors’ reports with the linguistic rules. Findings – It was found that the standardized illustrations of modified reports are not fully understandable by users of financial statements. The illustrations of modified auditors’ reports are not compliant with several linguistic rules. Originality/value – This paper provides new original investigation about the linguistic features of illustrations provided by the ISA 705 and ISA 706. This paper discusses the level of unintelligibility of standardized auditors’ reports and the implications for stakeholders.

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