Accurate moving target location in SAR imagery

2007 ◽  
Author(s):  
G.J. Vigurs ◽  
C. Milner ◽  
M.L. Jarrett
Keyword(s):  
Target Location ◽  
Moving Target ◽  
Sar Imagery

The Wandering Eye: An Eye Tracking Approach to Mind Wandering

2018 ◽  
Author(s):  
Jessica Schnabel
Keyword(s):  
Eye Tracking ◽  
Task Performance ◽  
Target Location ◽  
External Environment ◽  
Mind Wandering ◽  
Individual Characteristics ◽  
Moving Target ◽  
Tracking Data ◽  
The Mind

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.

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 The Feasibility Analysis of Aerial Moving Target Location Based on TDOA/FDOA/DSF Measurements

2012 ◽  
Vol 29 ◽  
pp. 785-790
Author(s):  
Bing Deng ◽  
Jinyu Xiong ◽  
Changxiong Xia
Keyword(s):  
Target Location ◽  
Feasibility Analysis ◽  
Moving Target

Optimal Size Fuzzy Models

2007 ◽  
Vol 11 (3) ◽  
pp. 335-341 ◽  
Author(s):  
Tamás D. Gedeon ◽  
◽  
László T. Kóczy ◽  
Alessandro Zorat ◽  
◽  
...  
Keyword(s):  
Target Location ◽  
Fuzzy Rule ◽  
Computation Time ◽  
Rule Base ◽  
Optimal Size ◽  
Moving Target ◽  
Trade Off ◽  
Base Size ◽  
Target Localisation ◽  
Time Required

Approximate models using fuzzy rule bases can be made more precise by suitably increasing the size of the rule base and decreasing uncertainty in the rules. A large rule base, however, requires more time for its evaluation and hence the problem arises of determining the size that is good enough for the task at hand, but allows as fast as possible reasoning using the rule base. This trade-off between computation time and precision is significant whenever a prediction is made which can become “out of date” or “too old” if not used in time. The trade off is considered here in the context of tracking a moving target. In this problem, a higher degree of accuracy results in tighter precision of determining target location, but at the cost of longer computation time, during which the target can move further away, thus ultimately requiring a longer search for exact target localisation. This paper examines the problem of determining the optimal rule base size that will yield a minimum total time required to repeatedly re-acquire the moving target, as done by a cat that plays with a mouse. While this problem has no known solution in its general formulation, solutions are shown here for specific contexts.

scholarly journals Interceptive capturing in large-billed crows: Velocity-dependent weighing of prediction of future target location and visual feedback of current target location

2020 ◽  
Author(s):  
Yusuke Ujihara ◽  
Hiroshi Matsui ◽  
Ei-Ichi Izawa
Keyword(s):  
Visual Feedback ◽  
Target Location ◽  
Target Position ◽  
Head Movements ◽  
Target Velocity ◽  
Moving Target ◽  
Tight Coupling ◽  
Motor Systems ◽  
Feedback Mechanisms ◽  
Behavioural Experiment

AbstractInterception of a moving target is a fundamental behaviour of predators and requires tight coupling between the sensory and motor systems. In the literature of foraging studies, feedback mechanisms based on current target position are frequently reported. However, there have also been recent reports of animals employing feedforward mechanisms, in which prediction of future target location plays an important role. In nature, coordination of these two mechanisms may contribute to intercepting evasive prey. However, how animals weigh these two mechanisms remain poorly understood. Here, we conducted a behavioural experiment involving crows (which show flexible sensorimotor coordination in various domains) capturing a moving target. We changed the velocity of the target to examine how the crows utilised prediction of the target location. The analysis of moment-to-moment head movements and computational simulations revealed that the crows used prediction of future target location when the target velocity was high. In contrast, their interception depended on the current momentary position of the target when the target velocity was slow. These results suggest that crows successfully intercept targets by weighing predictive and visual feedback mechanisms, depending on the target velocity.

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