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

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.

scholarly journals Moving Target Relative Speed Estimation and Refocusing in Synthetic Aperture Radar Images

2012 ◽  
Vol 48 (3) ◽  
pp. 2426-2436 ◽  
Author(s):  
Thomas K. Sjogren ◽  
Viet T. Vu ◽  
Mats I. Pettersson ◽  
Anders Gustavsson ◽  
Lars M. H. Ulander
Keyword(s):  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Moving Target ◽  
Speed Estimation ◽  
Relative Speed ◽  
Radar Images ◽  
Aperture Radar

scholarly journals Analysis of Moving Object Imaging from Compressively Sensed SAR Data in the Presence of Dictionary Mismatch

2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
Ahmed Shaharyar Khwaja ◽  
Muhammad Naeem ◽  
Alagan Anpalagan
Keyword(s):  
Iterative Scheme ◽  
Reconstruction Error ◽  
Synthetic Aperture ◽  
Moving Target ◽  
Target Imaging ◽  
Cause Of Error ◽  
Moving Target Imaging ◽  
Velocity Mismatch ◽  
Object Imaging ◽  
Better Than

We present compressed sensing (CS) synthetic aperture radar (SAR) moving target imaging in the presence of dictionary mismatch. Unlike existing work on CS SAR moving target imaging, we analyze the sensitivity of the imaging process to the mismatch and present an iterative scheme to cope with dictionary mismatch. We analyze and investigate the effects of mismatch in range and azimuth positions, as well as range velocity. The analysis reveals that the reconstruction error increases with the mismatch and range velocity mismatch is the major cause of error. Instead of using traditional Laplacian prior (LP), we use Gaussian-Bernoulli prior (GBP) for CS SAR imaging mismatch. The results show that the performance of GBP is much better than LP. We also provide the Cramer-Rao Bounds (CRB) that demonstrate theoretically the lowering of mean square error between actual and reconstructed result by using the GBP. We show that a combination of an upsampled dictionary and the GBP for reconstruction can deal with position mismatch effectively. We further present an iterative scheme to deal with the range velocity mismatch. Numerical and simulation examples demonstrate the accuracy of the analysis as well as the effectiveness of the proposed upsampling and iterative scheme.

Sign in / Sign up

Export Citation Format

Share Document