Software GPS Receiver Architecture for Flexible GNSS Signal Processing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional GPS receivers rely heavily on dedicated hardware, such as ASICs, which are costly and inflexible, and require redesign for new GNSS systems like Galileo, necessitating a software-based solution with lower computational requirements.
Innovation Solution
A software-based GPS receiver architecture that eliminates the need for ASICs in the digital processing phase, using a DSP or CPU to implement all processing functions, with a focus on ultra-low power hardware implementation, allowing for efficient processing of direct-sequence spread spectrum signals by removing the IF carrier and applying a baseband low-pass filter, followed by down-sampling and Doppler frequency removal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dedicated hardware (ASIC) is used for GPS signal processing, then processing reliability and speed are improved, but device cost and inflexibility increase
Solution Approach 1:
The patent replaces dedicated hardware (ASIC) with a software-based processing system running on general-purpose processors. The signal processing functions that were previously implemented in fixed hardware are now performed through executable instructions, allowing the same hardware platform to be reconfigured for different GNSS systems (GPS, Galileo, GLONASS, etc.) without physical redesign.
Solution Approach 2:
The patent creates a universal processing platform that can handle multiple GNSS satellite systems and signal types. The receiver architecture uses a single hardware platform with software that can be configured to process signals from different satellite constellations, making the system adaptable to current and future GNSS standards without requiring dedicated hardware for each system.
2Productivity
If ASIC is used for digital processing, then processing speed is improved, but manufacturing cost and redesign complexity increase
Solution Approach 1:
The patent implements a dynamic software-based processing system where the processing algorithms can be updated and reconfigured through software updates rather than hardware redesign. This allows the processing speed and capabilities to be optimized through software compilation and execution on high-performance general-purpose processors, eliminating the need for expensive ASIC manufacturing and redesign cycles.
Solution Approach 2:
The patent changes the fundamental parameter of implementation from fixed hardware (ASIC) to flexible software. This parameter change allows the same physical hardware to achieve high processing speeds through optimized software algorithms while maintaining ease of manufacture and updateability, as software can be deployed and modified without changing the physical device.
3Adaptability or versatility
If software-based processing is used, then adaptability and cost-effectiveness are improved, but computational requirements and processing complexity increase
Solution Approach 1:
The patent segments the complex signal processing task into distinct functional modules that can be independently implemented and optimized in software. The processing is divided into stages including correlation, Doppler compensation, code phase tracking, and navigation message decoding, allowing each segment to be handled by specialized software routines that collectively manage the overall computational complexity.
Solution Approach 2:
The patent introduces an intermediary layer of signal processing that bridges the received RF signal and the final navigation solution. This intermediary processing stage performs critical functions such as carrier removal, Doppler shift compensation, and code correlation, which simplifies the subsequent processing steps and makes the overall software-based system more manageable despite the increased computational requirements.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables flexible and cost-effective GPS signal processing, adaptable to changing performance requirements, and compatible with new GNSS systems without the need for redesigning hardware accelerators.
Implementation Method 1
with an analog-to-digital converter, generating a sequence of digitized samples from an intermediate frequency (IF) signal
Implementation Method 2
removing an intermediate carrier frequency from and subsequently low pass filtering the sequence of digitized samples
Implementation Method 3
subsequent to and separately from producing a combined quasi-baseband signal, downsampling, synchronizing in time to and removing individually a residual frequency shift from the combined quasi-baseband signal
Data Source
AI summary
A receiver architecture for processing spread spectrum signals. The receiver has an RF front end to receive and down convert a broadcast signal to an intermediate frequency carrier. The IF signal is digitized and provided to a processor (which may be a software-driven DSP, an ASIC or other embodiment) for processing. A given IF carrier is removed and the signal is low pass filtered. The signal is provided to a number of channels, each, for example, correspond to a unique transmitter. On each channel the sample rate is reduced to a predetermined fixed rate with timing mismatch compensated. The Doppler frequency shift, as estimated for the channel, is removed succeedingly. A locally generated copy of the spreading code used by the transmitter is applied to the carrier and Doppler removed signal at the predetermined fixed sample rate. The de-spread signal is used to provide estimates of the Doppler shift and for subsequent sample selection. Pseudo-range and delta pseudo-range estimates from each channel are used to estimate, for example, the receiver's position.