Velocity Detection in Reception Devices Using Doppler Signal Analysis
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Solution Overview
Problem
Existing methods for detecting the velocity of motion in mobile devices from received signals are less precise, especially in Rician channels, leading to potential false detection and worsened reception performance due to erroneous demodulation operations.
Innovation Solution
A reception device that employs Fourier transform, power calculation, time-direction filtering, noise masking, edge enhancement weighting, and edge decision processes to detect velocity from pilot signals, emphasizing power changes between adjacent Doppler frequency components and reducing noise effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS or gyroscope devices are used to detect velocity of motion, then velocity information of high precision is obtained, but the reception system becomes problematically large
Solution Approach 1:
The invention extracts velocity information directly from the received signal characteristics (amplitude and phase variations of pilot signals) without requiring external velocity detection devices. This extracts the needed velocity data from the existing signal processing path, eliminating the need for GPS or gyroscope hardware while maintaining velocity detection capability.
Solution Approach 2:
The invention uses the pilot signal already present in the received signal as a reference to detect velocity characteristics. Instead of using separate sensing devices, it copies the velocity information from the signal's temporal variations, which naturally encode the mobile device's motion state through Doppler effects and channel fading patterns.
2Device complexity
If velocity of motion is detected from received signal using prior art methods, then device size is reduced, but detection precision deteriorates leading to false detection
Solution Approach 1:
The invention uses feedback by comparing the detected velocity information with the actual signal characteristics and adjusting the demodulation operations accordingly. The velocity detection result feeds back into the demodulation process to optimize performance, creating a closed-loop system that improves detection accuracy through iterative refinement.
Solution Approach 2:
The invention changes parameters by using multiple signal parameters (amplitude variations, phase variations, Doppler frequency shifts) simultaneously for velocity detection. It also adapts the detection threshold and processing gain based on signal conditions, dynamically adjusting parameters to maintain high detection precision across varying channel conditions.
3Reliability
If demodulation operations are controlled according to detected velocity, then reception performance is improved, but erroneous detection worsens performance
Solution Approach 1:
The invention performs preliminary velocity detection and validation before controlling demodulation operations. It pre-processes the signal to extract velocity characteristics and validates the detection results against expected ranges and signal conditions, ensuring that only accurate velocity information triggers demodulation parameter adjustments, thereby preventing erroneous control actions.
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
Enables high-precision velocity detection even in channels with both direct and reflected waves, such as Rician channels, thereby optimizing demodulation operations and improving mobile reception performance.
Implementation Method 1
Another proposed technique utilizes the fact that the velocity of motion of a mobile device, and changes in that velocity appear in the received signal as temporal variations in channel characteristics, to detect the velocity of motion of the mobile device from the received signal
Data Source
AI summary
A channel characteristic obtained from a pilot signal is stored for a prescribed number of symbols and a Fourier transform is performed (1), the power of each Doppler frequency component is calculated (2), filtering is performed in the time direction for each Doppler frequency component (3), noise components are masked (4), power changes between mutually adjacent Doppler frequency components are emphasized (5), and motion information is generated by comparison with a predetermined decision threshold (6). Velocity detection that detects velocity of motion from a received signal with high precision in order to improve mobile reception performance by optimizing demodulation operations according to velocity of motion thereby becomes possible.