Network-based Collaborative Navigation in GPS-Denied Environment

Abstract

Global Positioning System (GPS) has been used as a primary source of navigation in land and airborne applications. However, challenging environments cause GPS signal blockage or degradation, and prevent reliable and seamless positioning and navigation using GPS only. Therefore, multi-sensor based navigation systems have been developed to overcome the limitations of GPS by adding some forms of augmentation. The next step towards assured robust navigation is to combine information from multiple ground-users, to further improve the chance of obtaining reliable navigation and positioning information. Collaborative (or cooperative) navigation can improve the individual navigation solution in terms of both accuracy and coverage, and may reduce the system's design cost, as equipping all users with high performance multi-sensor positioning systems is not cost effective. Generally, 'Collaborative Navigation' uses inter-nodal range measurements between platforms (users) to strengthen the navigation solution. In the collaborative navigation approach, the inter-nodal distance vectors from the known or more accurate positions to the unknown locations can be established. Therefore, the collaborative navigation technique has the advantage in that errors at the user's position can be compensated by other known (or more accurate) positions of other platforms, and may result in the improvement of the navigation solutions for the entire group of users. In this paper, three statistical network-based collaborative navigation algorithms, the Restricted Least-Squares Solution (RLESS), the Stochastic Constrained Least-Squares Solution (SCLESS) and the Best Linear Minimum Partial Bias Estimation (BLIMPBE) are proposed and compared to the Kalman filter. The proposed statistical collaborative navigation algorithms for network solution show better performance than the Kalman filter.

Multisensor Navigation Systems: A Remedy for GNSS Vulnerabilities?

“…More recently, data driven filters as well as centralized and decentralized approaches are gaining prominence. These developments are an effort to address the challenges of network scalability and computational efficiency combined with an increasing demand for high performance positioning for safety and liability critical applications, [17,18,45,46,47,48].…”

A Small-Sized Locating Message for Cooperative Localization under Communication Constraint

“…While in our algorithm, through the similarity conversion, two relative measurements are integrated as if an absolute measurement occurred in agent 1. As a result, only one set of pseudoabsolute locating message Λ e (1,k), Λ e (1,k), κ (1,2) , κ (1,3) is generated by agent 1 and then spread across the network.…”

“…In order to share the exteroceptive measurement across the agents, they are usually converted into a locating message that contains the useful positioning elements for network flowing. In this paper, we pursue a new form of locating message that, (1) contains less elements; and, (2) has the approximate equal effect on CL as the SPSD.…”

Collaborative Navigation as a Solution for PNT Applications in GNSS Challenged Environments – Report on Field Trials of a Joint FIG / IAG Working Group

“…Collectively, a network of GNSS users (hereafter referred to as nodes) may be able to receive sufficient satellite signals, augmented by inter-nodal ranging measurements and other sensors, such as IMUs or active / passive imaging sensors, in order to form a joint position solution [15,17,18,22,25,26,46]. This network of GNSS users represents a distributed antenna aperture with large inter-element spacing, which has some advantages and also drawbacks.…”