The advancement of software radio technology has provided an opportunity for the design of performance-enhanced GNSS/GPS receivers that are more flexible and easier to develop than their FPGA or ASIC based counterparts. Filling a gap in the current literature on the subject, this highly practical re
Navigation Signal Processing for GNSS Software Receivers
β Scribed by Thomas Pany
- Publisher
- Artech House Publishers
- Year
- 2010
- Tongue
- English
- Leaves
- 372
- Series
- GNSS Technology and Applications
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
The advancement of software radio technology has provided an opportunity for the design of performance-enhanced GNSS/GPS receivers that are more flexible and easier to develop than their FPGA or ASIC based counterparts. Filling a gap in the current literature on the subject, this highly practical resource offers engineers an in-depth understanding of navigation signal detection and estimation algorithms and their implementation in a software radio. This unique book focuses on high precision applications for GNSS signals and an innovative RTK receiver concept based on difference correlators. CD-ROM Included! It contains time-savings, ready-to-use signal estimation and detection algorithms that engineers can quickly apply to their specific receiver development projects.
β¦ Table of Contents
Radio Navigation Signals - Signal Generation. Signal Propagation. Signal Conditioning. Motivation for a Generic Signal Model. Sampling. Deterministic Received Signal Model. Stochastic Noise Model. Short-Period Signal Model. Exemplary Signals. ; Software-Defined Radio - Definitions. Communication Radios. GNSS Software Receivers. Technology Evaluation and Discussion. ; GNSS Receiver Structure and Dataflow - GNSS Sample Handling. Module Diagram. Execution Flow. GNSS Reference Station Configuration. Discussion. ; Signal Estimation - Parameters of Interest. Nonrandom Parameter Estimation. LSQ Correlators/Discriminators. Data Reduction. Bayesian Approach. Squaring Loss Revisited. Numerical Simulation. Discussion. ; Signal Detection - Detection Principles. Detection Domains. Preprocessing. Clairvoyant Detector for Uniformly Distributed Phase. Energy Detector. Bayesian Detector. Generalized Likelihood-Ratio Detector. System-Detection Performance. Long Integration Times and Differential Detectors. Discussion. ; Sample Preprocessing - ADC Quantization. Noise-Floor Determination. ADC Requirements for Pulse Blanking. Handling Colored Noise. Sub-Nyquist Sampling.; Correlators - Correlator and Waveform-Based Tracking. Generic Correlator. Correlator Types with Illustration. Difference Correlators. Noisy Reference Signal for Codeless Tracking. Incorporating Colored Noise. Comparison of Finite and Infinite Sample Rates. ; Discriminators - Noncoherent Discriminators. S-Curve Shaping. Multipath Estimating Techniques. From Discriminator Noise to Position Accuracy. ; Receiver Core Operations - Test-System Configuration. Signal-Sample Bit Conversion. Resampling. Correlators. Fast Fourier Transform. Reality Check for Signal Tracking. Power Consumption. Discussion. ; GNSS SDR RTK System Concept - Technology Enablers. System Overview. Key Algorithms and Components. High-Sensitivity Acquisition Engine. Assisted Tracking. Low-Cost Pseudolites. RTK Engine. ; Exemplary Source Code - Intended Use. Setup. Routines. ; Appendix. Abbreviations. List of Symbols. About the Author. Index ;
β¦ Subjects
GNSS, signal processing
π SIMILAR VOLUMES
Many important GPS applications such as the positioning of wireless devices, tracking during ionospheric scintillation, and orbit determination of geostationary and high Earth orbit satellites require a GNSS (global navigation satellite system) receiver with the ability to work with weak signals. Th
<span>Build and operate multi-GNSS and multi-frequency receivers with state-of-the-art techniques using this up-to-date, thorough, and easy-to-follow text. Covering both theory and practise, and complemented by MATLABΒ© code and digital samples with which to test it, this package is a powerful learni