Project description :
English Synthetized Version (21 lines) :
The main objective is to solve present technological limitations and scientific challenges related to GPS-Denied navigation for indoor environments, autonomously, without any external infrastructures (WiFi, GSM, RFID, etc.). Promising new digital signal processing architectures and methods will be investigated to enable indoor tridimensional precise positioning, navigation and to determine robust 3D spatial attitude of an autonomous GNSS receiver. This receiver will dynamically evolve in extremely weak navigation satellite signal scenarios (so-called “indoor”). The program will exploit notably system redundancy, new properties and possibilities of existing new GNSS signals. To enable such new capabilities, the methodology will investigate first the advantages of using a multi-antenna GNSS receiver. This in-house receiver has all capabilities to receive any kind of available GNSS signals from multiple antennas (typically 2 to 8). GNSS signal and frequency diversity analysis along with multipath signals and high sensitivity processing will be investigated using a patented and fully “open-design” universal GNSS architecture. The second major initiative will be conducted based on the principles derived from the telecommunication cognitive radio (CR) technology. This unique receiver will be referred to as the “intelligent Multi-Antennas Cognitive GNSS Receiver (iMACGR)”. A third investigation will aim to evaluate benefits of using raw measurements from very low cost inertial sensors such as 3D gyroscope, accelerometer and magnetometer, with adaptive learning processes to assist the iMACGR indoors. Several potential billion dollar industries will emerge by these GPS-Denied applications. The results of this program will open a completely new area of applications with GNSS navigation and reliable attitude determination indoors. This research program will strongly contribute towards new indoor guidance capabilities and businesses, new applications and security improvements for first responders, tourism, medical, defense and transportation industries, etc. This research program will directly be profitable to other numerous applications and engineering fields, including telecommunications and geomatic sciences.
2- Research program objectives
The overall goal of this research program is to increase and to extend the functioning capabilities of a cognitive GNSS receiver for indoor use by developing new methods and algorithms and evaluating its improved performance in real-time, real-world scenarios and environments. The proposed approach to this complex problem consists of exploiting GNSS diversity characteristics and modulation structure attributes [1] in a multi-antenna configuration, using CR methods and metrics adapted to GNSS receivers aided by appropriate low cost inertial measurements and attitude determination algorithms. The short-term objectives are to develop new CR metrics adapted to GNSS receiver architecture, to embed proper digital signal processing (DSP) in real-time, and to analyse the quantitative performance measurements. These new embedded metrics will take into account the special characteristics of existing GNSS signals. Improving currently available and developing new HS GPS algorithms will be continued. The developed GNSS cognitive metrics will also be used for assessing subsystem performance quality such as, monitoring, evaluating research and establishing success criteria during each milestone objective. The medium-term objectives are to improve SNR and sensitivity by investigating wideband multi-antenna direct and multipath GNSS signal processing techniques towards the goal of acquisition and tracking ultra-weak signals. HS analysis of GNSS receiver design research shall continue with multi-antenna algorithmic developments adding inertial attitude orientation of the tracking device. The long-term objective is to integrate the subset technologies within the laboratory prototype to exploit new capabilities, to study and to analyze its improved performance. Indoor multipath raw GNSS signal measurements from four antennas will be combined with inertial measurements to provide more reliable attitude determination and positioning. This aiding information will help the GNSS signal acquisition and tracking engine to output precise and robust indoor positioning and navigation information. Main long-term objective of this research program is to design an operational multi-antenna GNSS receiver which has cognitive intelligence capabilities aided by low cost inertial sensors so that ubiquitous indoor navigation is possible. The autonomous receiver will be intelligent (auto adaptable depending on the environment) and will be able to overcome limitations of signal availability, accuracy, integrity while adding resistance to various types of interference using CR spectrum management. This type of receiver will be patented and establish proof as a ‘gold standard of robustness’ in the field of ultra HS-GNSS receiver. This program will contribute substantially to the science of GNSS receiver design and related applications.
Research Objectives: 1) to develop new digital signal processing algorithms for high sensitivity without the help of other infrastructure, 2) to implement GNSS high sensitivity acquisition and tracking loops (including metrics in the development of the receiver cognition layer) using cognitive radio perception-learning algorithms of the environment, followed by executing actions, leveraging methods of dynamic programming to maximize information gain, 3) to use cognitive radio machine-learning algorithms to perform intelligent selection of channels and satellite signals in order to perform measurement fusion of multiple GNSS signals, 4) measure the performance benefits of new cognitive high sensibility methods and algorithms.
