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

CSSR: a 2For1 Compressive Sensing Software Receiver with Combined Correlation For GPS-CA and Galileo-OS Signals

This is a 2for1 receiver because it acquires both GPS and Galileo signals at less than 50% of the complexity and processing time required by a Matched Filter acquisition receiver. CSSR is a new implementation of a dual-GNSS-signal Software Receiver using, for the first time, the compressive sensing technique to process the two GNSS signals at the same time (in this implementation, GPS C/A code and Galileo OS code signals are used). This paper describes this CSSR implementation, focusing on: (a) how we remove the subcarrier frequency effect from the Galileo signal, and combine it with the GPS signal as a BPSK like signal; (b) the pre-processing stage of the resultant BPSK signal to generate the non-Doppler shift vectors that compensates for the matching measurements in the compressive sensing process; and finally (c) the compressive sensing process to acquire both signals simultaneously by combining their dictionaries, or correlators. CSSR has been simulated using various actual signal conditions/scenarios. The results are compared to those obtained from running the same tests on 3-other matched filter receivers. CSSR achieves similar probability of detection to the others, and has a higher frequency resolution of 10Hz for the same 4ms dwell time. With Application processors on-board Smartphones getting more powerful and cheaper, and with 60% of the 3.1 billion dual GNSS offering on-board current Smartphones are based on side-by-side implementations, we believe that CSSR is a good candidate to saving cost and valuable battery energy when implemented on-board Smartphones

OGSR: A Low Complexity Galileo Software Receiver using Orthogonal Data and Pilot Channels

To improve localisation accuracy and multipath rejection, the Galileo-OS signal offers a new modulation with efficient power distribution technique between the two data and pilot navigation components. To achieve the full benefits of this modulation, a robust acquisition and tracking methods must be deployed. For example, using two parallel correlation channels to acquire these data and pilot will gain 3dB over using a single channel acquisition correlating with either one of them. However, dual channel SW receivers cost more processing overheads. In this paper, the authors propose to orthogonalise the received data and pilot signals so to enable their acquisition in a single correlation channel bandpass sampling receiver. Our simulation results, using Simulink, prove that OGSR performance is maintained (preserving the 3dB gain) with less processing time while the implementation complexity is reduced by 50%

Balancing Compression and Encryption of Satellite Imagery

With the rapid developments in the remote sensing technologies and services, there is a necessity for combined compression and encryption of satellite imagery. The onboard satellite compression is used to minimize storage and communication bandwidth requirements of high data rate satellite applications. While encryption is employed to secure these resources and prevent illegal use of image sensitive information. In this paper, we propose an approach to address these challenges which raised in the highly dynamic satellite based networked environment. This approach combined compression algorithms (Huffman and SPIHT) and encryptions algorithms (RC4, blowfish and AES) into three complementary modes: (1) secure lossless compression, (2) secure lossy compression and (3) secure hybrid compression. The extensive experiments on the 126 satellite images dataset showed that our approach outperforms traditional and state of art approaches by saving approximately (53%) of computational resources. In addition, the interesting feature of this approach is these three options that mimic reality by imposing every time a different approach to deal with the problem of limited computing and communication resources

A Single Acquisition Channel Receiver for GPS L1CA and L2C Signals Based on Orthogonal Signal Processing

The GPS L1CA and L2C signals are transmitted from the same GPS Satellite Vehicles constellation. It is desirable, especially in commercial GNSS receivers, to have both of these signals acquired by a single receiver so to assure better signal acquisition and improved reliability at wider operating areas. To achieve this in an efficient process, we propose to integrate the GPS L1CA and L2CM signals orthogonally and acquire them in a single processing channel. After removing the Doppler frequency, our receiver first adds the quadrature components of the L2CM signal and the L1CA signal. This new signal is then shifted by 90o. This is then added to the remaining components of these two signals; thus resulting in an orthogonal form of the combined signals. Secondly, the FFT of this orthogonal signal is then mixed with the complex conjugate of the FFT of a locally generated replica of the CA code combined with a 90o-shifted replica of the CM code. Finally, the output signal is then converted back to the time domain to acquire the signal’s peak. The complexity of our dual-signal receiver implementation is half of that used in dual acquisition methods. Furthermore, MATLAB Simulation results show that our acquisition method compares favorably with other approaches in terms of detection of low sensitivity signals and false alarm probability

Galileo Signals Acquisition Using Enhanced Subcarrier Elimination Conversion and Faster Processing

To solve multipath and to enhance the localisation accuracy in a harsh environment, BOC modulation has been adopted in modern GNSS transmission, such as GPS-M-code and Galileo-OS-code signals. The designers of the BOC technique have pointed out that the correlation function becomes ambiguous when the received signal is correlated with the reference BOC signal at code phase resolutions of 0.5 Chip. This has motivated many contributions to resolving this ambiguity, for example, by processing each side of the BOC lobes as a BPSK signal. Our literature survey concluded that solutions claiming to have mitigated this ambiguity actually have resulted in a more complex receiver implementation. The Enhanced Subcarrier Elimination (ESCE) method detailed in this paper proposes combining the two side lobes into a single lobe centered at the main frequency, thus gaining 2dB more signal power as well as reducing the correlation requirements (signal’s mixing and transforming operations) to the half; i.e. accelerating the acquisition process. HaLo-430 platform generated signals used for testing the MATLAB model of ESCE proves that we outperform three of the most used unambiguous methods

Studies of p53 tumor suppression activity in mouse models

The p53 pathway is inactivated in essentially all human tumors; p53 is lost or mutated in over 50% of all human cancers, and the majority of the remaining tumors carry mutations in other components of the pathway. It appears that the main biological function of p53 in vivo is to suppress tumorigenesis, because mice with homozygous deletion of the p53 gene are normal, but develop multiple tumors at an early age, p53 plays a central role in cell cycle control and apoptosis in response to DNA damage and other stresses, and in response to oncogenic activation. Loss of p53 function leads to excessive proliferation due to an inappropriate cell cycle control, or to a reduced apoptosis and an excess survival. This allows propagation of cells with damaged DNA resulting in increased genetic instability and enhanced risk of cancer. The contribution of each of the p53 functions, or the lack thereof, to tumor initiation and progression has been studied in vivo, in genetically modified mice. Mice with deletions of one or both p53 alleles have been crossed with mice expressing dominant oncogenes, or lacking other tumor suppressor genes, in order to analyse the genetic interaction between different tumorigenic pathways in vivo. These studies have defined how oncogenic mutations can cooperate in tumorigenesis in tissue and the tumor-specific ways.Peer Reviewe

Typic Xerofluvents. Serie Reverte. Área de estudio: La Rinconada

3 páginas.-- Estudio realizado en el CEBAC, a petición de la Comunidad de Regantes del Canal del Valle Inferior del Guadalquivir.-- En el IRNAS se encuentran las publicaciones citadas para su consulta.-- Este documento también se encuentra en la base de datos de Evenor-TEch (Spin-off del CSIC).-- http://www.evenor-tech.com/banco/seisnet/seisnet.htm que incluye versiones en tres idiomas más.CEBAC-CSICPeer reviewe