Distance Meter Sampling Rate Shifts for Anti-Aliasing Precision
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Solution Overview
Problem
Existing distance measurement methods face challenges with signal sampling and reconstruction, particularly when dealing with changing or distorted signals, leading to aliasing effects that reduce measurement accuracy and require complex filtering or high-order filters to comply with the Nyquist theorem.
Innovation Solution
The method employs different sampling rates for signal sampling, shifting the relative positions of sampling points to optimize signal capture, allowing for high-precision measurements without extensive filtering, and enables the use of higher-frequency components by adapting sampling rates to match signal characteristics, thereby eliminating aliasing effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If signal sampling is performed with a fixed sampling rate, then the sampling process is simple, but aliasing effects occur that reduce measurement accuracy
Solution Approach 1:
The patent applies dynamics by making the sampling rate variable rather than fixed. The sampling rate is adapted dynamically based on the detected signal characteristics, particularly the signal bandwidth and frequency content. This allows the system to optimize measurement accuracy for different signal conditions without requiring a uniformly high sampling rate across all conditions, thus improving precision while managing complexity.
Solution Approach 2:
The patent changes the sampling rate parameter according to the signal characteristics. By detecting the signal bandwidth and adjusting the sampling rate accordingly (ensuring it exceeds twice the signal bandwidth), the system optimizes the balance between measurement accuracy and sampling complexity for each specific measurement condition.
2Measurement precision
If high-order filters are used to comply with the Nyquist theorem, then aliasing effects are reduced, but the device complexity and filtering effort increase
Solution Approach 1:
The patent performs preliminary detection of signal characteristics (bandwidth, frequency content) before the sampling process. Based on this preliminary information, the sampling rate is pre-adjusted to be sufficiently high (more than twice the signal bandwidth), which prevents aliasing effects without requiring complex post-sampling filtering. This preliminary adaptation eliminates the need for high-order anti-aliasing filters.
Solution Approach 2:
The system changes the sampling rate parameter dynamically based on detected signal characteristics. By adapting the sampling rate to match the actual signal bandwidth, the system ensures compliance with the Nyquist theorem without requiring fixed high-order filtering, thus reducing filtering effort while maintaining signal reconstruction accuracy.
3Measurement precision
If the sampling rate is increased to capture higher-frequency signal components, then measurement accuracy improves, but the requirements for analog-to-digital converters and processing speed increase
Solution Approach 1:
The patent implements dynamic sampling rate adjustment based on the actual signal characteristics. The sampling rate is increased only when the signal contains higher-frequency components that require it, and reduced when the signal bandwidth is narrower. This dynamic adaptation allows the system to achieve high measurement precision when needed while reducing converter and processing requirements during normal operation.
Solution Approach 2:
The sampling rate parameter is changed adaptively according to the detected signal bandwidth and frequency content. This ensures that the sampling rate is sufficiently high to capture all relevant signal components for accurate measurement, while avoiding unnecessarily high sampling rates that would increase converter and processing requirements without providing additional benefit.
4Measurement precision
If filtering is applied to reduce signal bandwidth before sampling, then the Nyquist condition can be fulfilled, but measurement accuracy may be compromised due to signal distortion
Solution Approach 1:
The patent inverts the conventional approach by not filtering the signal down to meet the Nyquist condition, but rather adjusting the sampling rate up to satisfy the Nyquist condition for the actual signal bandwidth. This inversion eliminates the need for signal-filtering that could distort the signal, while still ensuring accurate sampling and measurement.
Solution Approach 2:
Instead of changing the signal bandwidth through filtering, the patent changes the sampling rate parameter to match the signal characteristics. This approach preserves signal integrity by avoiding filtering-induced distortion while ensuring the sampling rate is sufficiently high to accurately capture the signal for precise distance measurement.
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 ensures accurate distance measurements in the mm or sub-mm range with a simple structure, even with non-linearly distorted pulses, and allows for precise signal reconstruction without the need for extensive filtering, enhancing measurement precision and flexibility.
Implementation Method 1
A measurement signal source 1 for emitting at least one measurement signal MS, in particular a light signal
Implementation Method 2
receive and evaluate the reflected signal component as a target signal
Implementation Method 3
sampling the target signal with different sampling rates, so that the relative positions of the sampling points with respect to the signal are shifted
Implementation Method 4
the distance to the target to be measured being determined using the transit time of the pulse
Data Source
Figure 1~3
Figure 4~5
Figure 6a~6b
AI summary
The invention relates to a distance measuring method comprising at least the step of emitting at least one measurement signal to a target object, in which at least one start signal (S) is produced, and the measurement signal is back scattered from the target object as a target signal (Z). Said target signal (Z) and optionally also the start signal (S) is sampled in a first and a second sampling at various sampling rates and determines the distance to the target object from the relative position from the start signal (S) and target signal (Z).