Random Sampling System Based on Target Information Distribution Pattern

A technology of distribution pattern and target information, applied in the field of signal detection and information acquisition, which can solve problems such as Nyquist distribution sampling aliasing

Active Publication Date: 2020-09-08
中科观世(北京)科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the practice of "compressed sampling" theory, it is found that the Nyquist distribution sampling in "compressed sampling" will still follow the law of sampling theorem and appear "aliasing" phenomenon

Method used

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  • Random Sampling System Based on Target Information Distribution Pattern
  • Random Sampling System Based on Target Information Distribution Pattern
  • Random Sampling System Based on Target Information Distribution Pattern

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0095] Embodiment 1: Spectrum analysis of audio signal

[0096] See attached Figure 3-6 , with Figure 7-8 ;Compared with the sampling rate of Nyquist distribution through Y distribution mode sampling: when the Nyquist distribution sampling rate is 44.1KHz, high-fidelity sound effects can be obtained; while the same sound effect is sampled with Y distribution mode, The normal distribution sampling rate only needs to be 400Hz, and a data set with a distortion error of less than 0.3% can be obtained when the Nyquist distribution sampling rate is 44.1KHz. The normal distribution in the Y distribution mode produces the solution with the highest fitness, and we output this solution to obtain a minimum sampling rate of 400Hz, and the restored signal does not produce aliasing. The conclusion is that compared with sampling in the Y distribution mode and sampling in the Nyquist distribution mode, the data sampled in the Y distribution mode still maintains the same resolution of th...

Embodiment 2

[0097] Example 2: Figure 13-14 . When sampling a frequency, if the frequency points are close together, for example: two audio signals of 233.5Hz and 233.6Hz are mixed together, use the Nyquist sampling method to distinguish the two frequencies, The sampling frequency must be calculated to distinguish the difference of 0.1Hz. To distinguish the 0.1Hz difference in 233.6Hz, it is necessary to achieve a difference of at least 1Hz between the two frequencies, and to distinguish the 1Hz difference, the current audio signal The sampling frequency must be ≥ 233.6Hz × 10 × 2 = 4672Hz; when we sample with a sampling frequency < 4672Hz, the result will be aliasing, and the two frequencies will be difficult to distinguish. When the uniform distribution, normal distribution and Rayleigh distribution sampling methods are used, the same sampling point can be used to obtain the result of accurately separating the frequencies.

Embodiment 3

[0098] Example 3: Figure 15-16 . If the two audio signals of 678.5Hz and 678.6Hz are mixed together, and the two frequencies are distinguished by the Nyquist sampling method, the sampling frequency must be ≥ 678.6Hz×10×2=13570Hz; when we use < When sampling at a sampling frequency of 13570Hz, aliasing occurs as a result, making it difficult to distinguish between the two frequencies. When the uniform distribution, normal distribution and Rayleigh distribution sampling methods are used, the same sampling point can be used to obtain the result of accurately separating the frequencies.

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Abstract

The invention discloses a random sampling system based on an information distribution mode. The system for adaptively establishing similarly distributed random sampling points for original signal collection is established. The system is composed of a computer, a signal sensor, a signal collection module and an FIFO module. When Y distribution mode sampling and Nyquist mode sampling are carried out, under the same data quantity, the signal resolution obtained by the Y distribution mode sampling is higher that obtained by the Nyquist mode sampling, so original signals of different distribution modes can be separated from a near field microwave detection scene; and under the condition that the same signal resolution obtained by relatively high Nyquist sampling frequency is still kept, the data quantity of the Y distribution mode sampling can be greatly reduced.

Description

technical field [0001] The invention belongs to the technical field of signal detection and information acquisition, and in particular relates to a pseudo-random sampling technology established based on an information distribution pattern. Background technique [0002] Sampling is a method of converting an original signal (ie, a continuous function in time or space) into a numerical sequence (ie, a discrete function in time or space). The collection point where the original signal data is collected at the corresponding time is called the sampling point, the sampling process of the sample is called the sample sampling, and each sampled signal value is called a sampling sample; the time gap between two sampling points is called the sampling interval ;The time interval of signal sampling is very small, generally on the order of milliseconds and microseconds; the time function of the sampling point is x(t), and the signal data collected at the sampling point is the signal level,...

Claims

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Application Information

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Patent Type & AuthorityPatents(China)
IPC IPC(8): H04R3/00
CPCH04R3/00H04R2430/00
Inventor姚萌苏勇飞叶征宇
Owner中科观世(北京)科技有限公司