What effect does network size have on NRTK positioning?

The Network Real Time Kinematic (NRTK) positioning is nowadays a very common practice not only in academia but also in the professional world. To support the users several networks of Continuous Operating Reference Stations (CORSs) were born. These networks offer real-time services for NRTK positioning, providing a centimetric positioning accuracy with an average distance of 25-35 kms between the reference stations. But what is the effective distance between reference stations that allows to achieve the precision required for real-time positioning, using both geodetic and GIS receivers? How the positional accuracy changes with increasing distances between CORS? Can a service of geostationary satellites, such as the European EGNOS, be an alternative to the network positioning for medium-low cost receivers? These are only some of the questions that the Authors try to answer in this articl

A scheme for weak GPS signal acquisition aided by SINS information

In order to enhance the acquisition performance of global positioning system (GPS) receivers in weak signal conditions, a high-sensitivity acquisition scheme aided by strapdown inertial navigation system (SINS) information is proposed. The carrier Doppler shift and Doppler rate are pre-estimated with SINS aiding and GPS ephemeris, so that the frequency search space is reduced, and the dynamic effect on the acquisition sensitivity is mitigated effectively. Meanwhile, to eliminate the signal-to-noise ratio gain attenuation caused by data bit transitions, an optimal estimation of the unknown data bits is implemented with the Viterbi algorithm. A differential correction method is then utilized to improve the acquisition accuracy of Doppler shift and therefore to meet the requirement of carrier-tracking loop initialization. Finally, the reacquisition experiments of weak GPS signals are implemented in short signal blockage situations. The simulation results show that the proposed scheme can significantly improve the acquisition accuracy and sensitivity and shorten the reacquisition time. © 2013 Springer-Verlag Berlin Heidelberg

Multi-GNSS signals acquisition techniques for software defines receivers

Any commercially viable wireless solution onboard Smartphones should resolve the technical issues as well as preserving the limited resources available such as processing and battery. Therefore, integrating/combining the process of more than one function will free up much needed resources that can be then reused to enhance these functions further. This thesis details my innovative solutions that integrate multi-GNSS signals of specific civilian transmission from GPS, Galileo and GLONASS systems, and process them in a single RF front-end channel (detection and acquisition), ideal for GNSS software receiver onboard Smartphones. During the course of my PhD study, the focus of my work was on improving the reception and processing of localisation techniques based on signals from multi-satellite systems. I have published seven papers on new acquisition solutions for single and multi-GNSS signals based on the bandpass sampling and the compressive sensing techniques. These solutions, when applied onboard Smartphones, shall not only enhance the performance of the GNSS localisation solution but also reduce the implementation complexity (size and processing requirements) and thus save valuable processing time and battery energy. Firstly, my research has exploited the bandpass sampling technique, if being a good candidate for processing multi-signals at the same time. This portion of the work has produced three methods. The first method is designed to detect the GPS, Galileo and GLONASS-CDMA signals’ presence at an early stage before the acquisition process. This is to avoid wasting processing resources that are normally spent on chasing signals not present/non-existent. The second focuses on overcoming the ambiguity when acquiring Galileo-OS signal at a code phase resolution equal to 0.5 Chip or higher and this achieved by multiplying the received signal with the generated sub-carrier frequency. This new conversion saves doing a complete correlation chain processing when compared to conventionally used methods. The third method simplifies the joining implementation of the Galileo-OS data-pilot signal acquisition by constructing an orthogonal signal so as to acquire them in a single correlation chain, yet offering the same performance as using two correlation chains. Secondly, the compressive sensing technique is used to acquire multi-GNSS signals to achieve computation complexity reduction over correlator based methods, like Matched Filter, while still maintaining acquisition integrity. As a result of this research work, four implementation methods were produced to handle single or multi-GNSS signals. The first of these methods is designed to change dynamically the number and the size of the required channels/correlators according to the received GPS signal-power during the acquisition process. This adaptive solution offers better fix capability when the GPS receiver is located in a harsh signal environment, or it will save valuable processing/decoding time when the receiver is outdoors. The second method enhances the sensing process of the compressive sensing framework by using a deterministic orthogonal waveform such as the Hadamard matrix, which enabled us to sample the signal at the information band and reconstruct it without information loss. This experience in compressive sensing led the research to manage more reduction in terms of computational complexity and memory requirements in the third method that decomposes the dictionary matrix (representing a bank of correlators), saving more than 80% in signal acquisition process without loss of the integration between the code and frequency, irrespective of the signal strength. The decomposition is realised by removing the generated Doppler shifts from the dictionary matrix, while keeping the carrier frequency fixed for all these generated shifted satellites codes. This novelty of the decomposed dictionary implementation enabled other GNSS signals to be combined with the GPS signal without large overhead if the two, or more, signals are folded or down-converted to the same intermediate frequency. The fourth method is, therefore, implemented for the first time, a novel compressive sensing software receiver that acquires both GPS and Galileo signals simultaneously. The performance of this method is as good as that of a Matched Filter implementation performance. However, this implementation achieves a saving of 50% in processing time and produces a fine frequency for the Doppler shift at resolution within 10Hz. Our experimental results, based on actual RF captured signals and other simulation environments, have proven that all above seven implementation methods produced by this thesis retain much valuable battery energy and processing resources onboard Smartphones

Enhanced receiver architectures for processing multi GNSS signals in a single chain : based on partial differential equations mathematical model

The focus of our research is on designing a new architecture (RF front-end and digital) for processing multi GNSS signals in a single receiver chain. The motivation is to save in overhead cost (size, processing time and power consumption) of implementing multiple signal receivers side-by-side on-board Smartphones. This thesis documents the new multi-signal receiver architecture that we have designed. Based on this architecture, we have achieved/published eight novel contributions. Six of these implementations focus on multi GNSS signal receivers, and the last two are for multiplexing Bluetooth and GPS received signals in a single processing chain. We believe our work in terms of the new innovative and novel techniques achieved is a major contribution to the commercial world especially that of Smartphones. Savings in both silicon size and processing time will be highly beneficial to reduction of costs but more importantly for conserving the energy of the battery. We are proud that we have made this significant contribution to both industry and the scientific research and development arena. The first part of the work focus on the Two GNSS signal detection front-end approaches that were designed to explore the availability of the L1 band of GPS, Galileo and GLONASS at an early stage. This is so that the receiver devotes appropriate resources to acquire them. The first approach was based on folding the carrier frequency of all the three GNSS signals with their harmonics to the First Nyquist Zone (FNZ), as depicted by the BandPass Sampling Receiver technique (BPSR). Consequently, there is a unique power distribution of these folded signals based on the actual present signals that can be detected to alert the digital processing parts to acquire it. Volterra Series model is used to estimate the existing power in the FNZ by extracting the kernels of these folded GNSS signals, if available. The second approach filters out the right-side lobe of the GLONASS signal and the left-side lobe of the Galileo signal, prior to the folding process in our BPSR implementation. This filtering is important to enable none overlapped folding of these two signals with the GPS signal in the FNZ. The simulation results show that adopting these two approaches can save much valuable acquisition processing time. Our Orthogonal BandPass Sampling Receiver and Orthogonal Complex BandPass Sampling Receiver are two methods designed to capture any two wireless signals simultaneously and use a single channel in the digital domain to process them, including tracking and decoding, concurrently. The novelty of the two receivers is centred on the Orthogonal Integrated Function (OIF) that continuously harmonies the two received signals to form a single orthogonal signal allowing the “tracking and decoding” to be carried out by a single digital channel. These receivers employ a Hilbert Transform for shifting one of the input signals by 90-degrees. Then, the BPSR technique is used to fold back the two received signals to the same reference frequency in the FNZ. Results show that these designed methods also reduce the sampling frequency to a rate proportional to the maximum bandwidth, instead of the summation of bandwidths, of the input signals. Two combined GPS L1CA and L2C signal acquisition channels are designed based on applying the idea of the OIF to enhance the power consumption and the implementation complexity in the existing combination methods and also to enhance the acquisition sensitivity. This is achieved by removing the Doppler frequency of the two signals; our methods add the in-phase component of the L2C signal together with the in-phase component of the L1CA signal, which is then shifted by 90-degree before adding it to the remaining components of these two signals, resulting in an orthogonal form of the combined signals. This orthogonal signal is then fed to our developed version of the parallel-code-phase-search engine. Our simulation results illustrate that the acquisition sensitivity of these signals is improved successfully by 5.0 dB, which is necessary for acquiring weak signals in harsh environments. The last part of this work focuses on the tracking stage when specifically multiplexing Bluetooth and L1CA GPS signals in a single channel based on using the concept of the OIF, where the tracking channel can be shared between the two signals without losing the lock or degrading its performance. Two approaches are designed for integrating the two signals based on the mathematical analysis of the main function of the tracking channel, which the Phase-Locked Loop (PLL). A mathematical model of a set of differential equations has been developed to evaluate the PLL when it used to track and demodulated two signals simultaneously. The simulation results proved that the implementation of our approaches has reduced by almost half the size and processing time

Ubiquitous health monitoring system for seniors

The Ubiquitous Health Monitoring System for Seniors is a prototype for an implantable module that is designed to eliminate critical delays in receiving medical attention upon the development of a heart attack. In particular, the prototype is to detect the onset of heart attacks in real time, and to use a Bluetooth wireless link to signal the patient\u27s mobile phone to dial emergency personnel in the event of an abnormality. The unit also records and logs the temperature of the user. Since the unit holds a GPS in it the current position of the user can be constantly monitored and by this the paramedics can arrive at the patient\u27s current location without any delay. The health monitoring system enables seniors to stay in their homes rather than in a medical institution which, in turn, cuts down the cost of medical care to a great extent