Stand-off Target Tracking using Line-of-Sight Distance Bifurcation

2022 ◽  
Author(s):  
Neon Srinivasu ◽  
Ashwini Ratnoo
Keyword(s):  
Target Tracking ◽  
Line Of Sight ◽  
Sight Distance

Line-of-sight rate modeling and error analysis of inertial stabilized platforms by coordinate transformation

2017 ◽  
Vol 233 (4) ◽  
pp. 1317-1322 ◽  
Author(s):  
Qingjia Gao ◽  
Qiang Sun ◽  
Feng Qu ◽  
Jiang Wang ◽  
Xizhen Han ◽  
...  
Keyword(s):  
Theoretical Model ◽  
Target Tracking ◽  
Coordinate Transformation ◽  
Servo Control ◽  
Line Of Sight ◽  
Measurement Equations ◽  
Stabilized Platform ◽  
First Time ◽  
Guidance Laws ◽  
Key Parameter

Line-of-sight rate is the key parameter that enables inertial stabilized platforms to implement guidance laws successfully for target tracking or attacking. It is always obtained by experiments. In this article, a theoretical model of the line-of-sight rate is established for the first time, starting with the gimbal motion. The strategy to acquire line-of-sight rate is based on the servo control circuit. The measurement equations for line-of-sight rate are derived using a coordinate transformation. An error model is then obtained with the help of differentiation. The error of an inertial stabilized platform prototype is measured, showing that the line-of-sight rate error can be predicted accurately. Finally, a high-precision inertial stabilized platform is successfully designed and analyzed, with the accuracy of 0.06°/s and 0.37°/s when line-of-sight rates are set to 1.5°/s and 9°/s, respectively.

Predicted Line-of-Sight Coordinate Approach to Target Tracking for Airborne AESA Radars

2020 ◽  
Vol 69 (6) ◽  
pp. 914-923
Author(s):  
Bo-Young Jung ◽  
Dahye Ham ◽  
Ui-Suk Suh ◽  
Won-Sang Ra ◽  
Boram Yoon ◽  
...  
Keyword(s):  
Target Tracking ◽  
Line Of Sight

Target tracking without line of sight using range from radio

2011 ◽  
Vol 32 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Geoffrey A. Hollinger ◽  
Joseph Djugash ◽  
Sanjiv Singh
Keyword(s):  
Target Tracking ◽  
Line Of Sight

Approximation of Capture Sets in Visibility-Based Target-Tracking Games for Non-Holonomic Players

2017 ◽  
Author(s):  
Rui Zou ◽  
Sourabh Bhattacharya
Keyword(s):  
Target Tracking ◽  
Computing Time ◽  
Line Of Sight ◽  
Differential Drive ◽  
Pursuit Evasion ◽  
Optimal Paths ◽  
Evasion Game ◽  
Time Optimal ◽  
Differential Drive Robot ◽  
Arbitrary Line

In this work, we analyze approximations of capture sets [1] for a visibility based pursuit-evasion game. In contrast to the capture problem, the pursuer tries to maintain a line-of-sight with the evader in free space in our problem. We extend the concept of U set initially proposed in [2] for holonomic players to the scenario in which the pursuer is holonomic. The problem of computing the U set is reduced to that of computing time-optimal paths for the non-holonomic vehicles to an arbitrary line. We characterize the primitives for time-optimal paths for the Dubin’s vehicle, Reed-shepps car and a Differential Drive robot. Based on these primitives, we construct the optimal paths and provide an algorithm to compute the U set.

Path Planning for Cooperative Line Of Sight Target Tracking of Heterogeneous Unmanned Marine Vehicle Teams

2009 ◽  
Vol 42 (18) ◽  
pp. 358-363 ◽  
Author(s):  
Thomas Glotzbach ◽  
Matthias Schneider ◽  
Peter Otto
Keyword(s):  
Path Planning ◽  
Target Tracking ◽  
Line Of Sight ◽  
Marine Vehicle

scholarly journals Multiple Drone Navigation and Formation Using Selective Target Tracking-Based Computer Vision

Electronics ◽  
2021 ◽  
Vol 10 (17) ◽  
pp. 2125
Author(s):  
Jatin Upadhyay ◽  
Abhishek Rawat ◽  
Dipankar Deb
Keyword(s):  
Computer Vision ◽  
Target Tracking ◽  
Line Of Sight ◽  
Tracking Accuracy ◽  
Ground Station ◽  
Image Center ◽  
Aerial Vehicle ◽  
Using Data ◽  
The One ◽  
The Individual

Autonomous unmanned aerial vehicles work seamlessly within the GPS signal range, but their performance deteriorates in GPS-denied regions. This paper presents a unique collaborative computer vision-based approach for target tracking as per the image’s specific location of interest. The proposed method tracks any object without considering its properties like shape, color, size, or pattern. It is required to keep the target visible and line of sight during the tracking. The method gives freedom of selection to a user to track any target from the image and form a formation around it. We calculate the parameters like distance and angle from the image center to the object for the individual drones. Among all the drones, the one with a significant GPS signal strength or nearer to the target is chosen as the master drone to calculate the relative angle and distance between an object and other drones considering approximate Geo-location. Compared to actual measurements, the results of tests done on a quadrotor UAV frame achieve 99% location accuracy in a robust environment inside the exact GPS longitude and latitude block as GPS-only navigation methods. The individual drones communicate to the ground station through a telemetry link. The master drone calculates the parameters using data collected at ground stations. Various formation flying methods help escort other drones to meet the desired objective with a single high-resolution first-person view (FPV) camera. The proposed method is tested for Airborne Object Target Tracking (AOT) aerial vehicle model and achieves higher tracking accuracy.

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