High-speed multi-dimensional relative navigation for uncooperative space objects

This work proposes a high-speed Light Detection and Ranging (LIDAR) based navigation architecture that is appropriate for uncooperative relative space navigation applications. In contrast to current solutions that exploit 3D LIDAR data, our architecture transforms the odometry problem from the 3D space into multiple 2.5D ones and completes the odometry problem by utilizing a recursive filtering scheme. Trials evaluate several current state-of-the-art 2D keypoint detection and local feature description methods as well as recursive filtering techniques on a number of simulated but credible scenarios that involve a satellite model developed by Thales Alenia Space (France). Most appealing performance is attained by the 2D keypoint detector Good Features to Track (GFFT) combined with the feature descriptor KAZE, that are further combined with either the H∞ or the Kalman recursive filter. Experimental results demonstrate that compared to current algorithms, the GFTT/KAZE combination is highly appealing affording one order of magnitude more accurate odometry and a very low processing burden, which depending on the competitor method, may exceed one order of magnitude faster computation

Bibliographic Review on Distributed Kalman Filtering

In recent years, a compelling need has arisen to understand the effects of distributed information structures on estimation and filtering. In this paper, a bibliographical review on distributed Kalman filtering (DKF) is provided.\ud The paper contains a classification of different approaches and methods involved to DKF. The applications of DKF are also discussed and explained separately. A comparison of different approaches is briefly carried out. Focuses on the contemporary research are also addressed with emphasis on the practical applications of the techniques. An exhaustive list of publications, linked directly or indirectly to DKF in the open literature, is compiled to provide an overall picture of different developing aspects of this area

Target Coordinates Estimation by Passive Radar with a Single non-Cooperative Transmitter and a Single Receiver

Passive radar is a bistatic radar that detects and tracks targets by processing reflections from non-cooperative transmitters. Due to the bistatic geometry for this radar, a target can be localized in Cartesian coordinates by using one of the following bistatic geometries: multiple non-cooperative transmitters and a single receiver, or a single non-cooperative transmitter and multiple receivers, whereas the diversity of receivers or non-cooperative transmitters leads to extra signal processing and a ghost target phenomenon. To mitigate these two disadvantages, we present a new method to estimate Cartesian coordinates of a target by a passive radar system with a single non-cooperative transmitter and a single receiver. This method depends on the ability of the radar receiver to analyze a signal-to-noise ratio (SNR) and estimate two arrival angles for the target’s echo signal. The proposed passive radar system is simulated with a Digital Video Broadcasting-Terrestrial (DVB-T) transmitter, and the simulation results show the efficiency of this system compared with results of other researches

Device Free Localisation Techniques in Indoor Environments

The location estimation of a target for a long period was performed only by device based localisation technique which is difficult in applications where target especially human is non-cooperative. A target was detected by equipping a device using global positioning systems, radio frequency systems, ultrasonic frequency systems, etc. Device free localisation (DFL) is an upcoming technology in automated localisation in which target need not equip any device for identifying its position by the user. For achieving this objective, the wireless sensor network is a better choice due to its growing popularity. This paper describes the possible categorisation of recently developed DFL techniques using wireless sensor network. The scope of each category of techniques is analysed by comparing their potential benefits and drawbacks. Finally, future scope and research directions in this field are also summarised

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available