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

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.

2020 ◽  
Vol 54 (1) ◽  
pp. 66-84
Author(s):  
Eppili Jaya ◽  
B.T. Krishna

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.


2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Renzheng Xue ◽  
Ming Liu ◽  
Xiaokun Yu

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.


2021 ◽  
Vol 21 (2) ◽  
pp. 161-164
Author(s):  
Ilkyu Kim ◽  
Hyun Kim ◽  
Jeong-Hae Lee

There have been considerable challenges with radar systems for detecting high-speed projectiles at a short range. This necessitates the presentation of a guideline for the minimum detection range that will guarantee detection of a target. In this letter, the detection range for a rapidly flying target is studied based on the characteristics of the target, such as speed and launch angle, and radar parameters such as pulse repetition interval, dwell time, beamwidth, and so on. The derived equation was applied to parametric studies for different characteristics of targets in order to investigate the influential parameters that affect the minimum detection range. A field test using the radar system’s prototype was performed to evaluate the validity of the proposed equation.


Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2391
Author(s):  
Marco Martorella ◽  
Samuele Gelli ◽  
Alessio Bacci

Ground moving target imaging finds its main applications in both military and homeland security applications, with examples in operations of intelligence, surveillance and reconnaissance (ISR) as well as border surveillance. When such an operation is performed from the air looking down towards the ground, the clutter return may be comparable or even stronger than the target’s, making the latter hard to be detected and imaged. In order to solve this problem, multichannel radar systems are used that are able to remove the ground clutter and effectively detect and image moving targets. In this feature paper, the latest findings in the area of Ground Moving Target Imaging are revisited that see the joint application of Space-Time Adaptive Processing and Inverse Synthetic Aperture Radar Imaging. The theoretical aspects analysed in this paper are supported by practical evidence and followed by application-oriented discussions.


Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 577
Author(s):  
Luca Schirru ◽  
Tonino Pisanu ◽  
Angelo Podda

Space debris is a term for all human-made objects orbiting the Earth or reentering the atmosphere. The population of space debris is continuously growing and it represents a potential issue for active satellites and spacecraft. New collisions and fragmentation could exponentially increase the amount of debris and so the level of risk represented by these objects. The principal technique used for the debris monitoring, in the Low Earth Orbit (LEO) between 200 km and 2000 km of altitude, is based on radar systems. The BIRALET system represents one of the main Italian radars involved in resident space objects observations. It is a bi-static radar, which operates in the P-band at 410–415 MHz, that uses the Sardinia Radio Telescope as receiver. In this paper, a detailed description of the new ad hoc back-end developed for the BIRALET radar, with the aim to perform slant-range and Doppler shift measurements, is presented. The new system was successfully tested in several validation measurement campaigns, the results of which are reported and discussed.


2015 ◽  
Vol 734 ◽  
pp. 203-206
Author(s):  
En Zeng Dong ◽  
Sheng Xu Yan ◽  
Kui Xiang Wei

In order to enhance the rapidity and the accuracy of moving target detection and tracking, and improve the speed of the algorithm on the DSP (digital signal processor), an active visual tracking system was designed based on the gaussian mixture background model and Meanshift algorithm on DM6437. The system use the VLIB library developed by TI, and through the method of gaussian mixture background model to detect the moving objects and use the Meanshift tracking algorithm based on color features to track the target in RGB space. Finally, the system is tested on the hardware platform, and the system is verified to be quickness and accuracy.


Author(s):  
Jessica Schnabel

Mind wandering, or “daydreaming,” is a shift in the contents of a thought away from a task and/or event in the external environment, to self-generated thoughts and feelings. This research seeks to test the reliability of eye tracking as an objective of measure mind wandering using the Wandering Eye Paradigm, as well as examine the relationships between mind wandering and individual characteristics. Fifty participants will be recruited for two appointments a day apart, on each day on each day completing two eye tracking sessions following a moving target. In this task, participants will be instructed to press the space bar if they feel they are mind wandering, and then answer three questions about their episode content. Questionnaires measuring mind wandering, procrastination, mindfulness, creativity and personality (in particular conscientiousness) will be completed between eye tracking sessions. By comparing the eye tracking data in the period prior to the spacebar press we can determine quantifiable indicators of the onset and duration of mind wandering episodes by analyzing gaze location in relation to the target location. It has been hypothesized that severity of task performance failures (losing track of the target) should correlate with the “depth” of the mind wandering episode content. Additionally, we expect the frequency of mind wandering episodes to correlate with individual characteristics, and that these measures will be consistent across trials. This research would provide a novel objective way to identify and measure mind wandering, and would help further advance the understanding of its behavioral and subjective dimensions.


2018 ◽  
Vol 119 (1) ◽  
pp. 221-234 ◽  
Author(s):  
Yuhui Li ◽  
Yong Wang ◽  
He Cui

As a vital skill in an evolving world, interception of moving objects relies on accurate prediction of target motion. In natural circumstances, active gaze shifts often accompany hand movements when exploring targets of interest, but how eye and hand movements are coordinated during manual interception and their dependence on visual prediction remain unclear. Here, we trained gaze-unrestrained monkeys to manually intercept targets appearing at random locations and circularly moving with random speeds. We found that well-trained animals were able to intercept the targets with adequate compensation for both sensory transmission and motor delays. Before interception, the animals' gaze followed the targets with adequate compensation for the sensory delay, but not for extra target displacement during the eye movements. Both hand and eye movements were modulated by target kinematics, and their reaction times were correlated. Moreover, retinal errors and reaching errors were correlated across different stages of reach execution. Our results reveal eye-hand coordination during manual interception, yet the eye and hand movements may show different levels of prediction based on the task context. NEW & NOTEWORTHY Here we studied the eye-hand coordination of monkeys during flexible manual interception of a moving target. Eye movements were untrained and not explicitly associated with reward. We found that the initial saccades toward the moving target adequately compensated for sensory transmission delays, but not for extra target displacement, whereas the reaching arm movements fully compensated for sensorimotor delays, suggesting that the mode of eye-hand coordination strongly depends on behavioral context.


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