CN111490789A - Periodic weak signal detection method and device based on pseudo median accumulation - Google Patents
Periodic weak signal detection method and device based on pseudo median accumulation Download PDFInfo
- Publication number
- CN111490789A CN111490789A CN202010295524.3A CN202010295524A CN111490789A CN 111490789 A CN111490789 A CN 111490789A CN 202010295524 A CN202010295524 A CN 202010295524A CN 111490789 A CN111490789 A CN 111490789A
- Authority
- CN
- China
- Prior art keywords
- median
- data
- sampling data
- pseudo
- unit
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
- H03M1/00—Analogue/digital conversion; Digital/analogue conversion
- H03M1/12—Analogue/digital converters
- H03M1/124—Sampling or signal conditioning arrangements specially adapted for A/D converters
- H03M1/1245—Details of sampling arrangements or methods
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Analogue/Digital Conversion (AREA)
Abstract
The invention discloses a periodic weak signal detection method and a device based on pseudo median accumulation, wherein a relevant scheme not only can detect periodic weak signals from noise, but also is not influenced by periodic weak interference signals of even-numbered times of sampling periods introduced in the sampling process; moreover, the median is a statistic for resisting extreme value interference, so the method has better robustness. In addition, there is a potential feature of this scheme: since the maximum value of the left-right difference has a positive correlation with the signal-to-noise ratio of the periodic weak signal, the periodic weak signal with a determined shape can also be used to estimate the signal-to-noise ratio of the signal.
Description
Technical Field
The invention relates to the technical field of signal processing, in particular to a periodic weak signal detection method and device based on pseudo-median accumulation.
Background
For a periodic weak Signal whose Signal-to-Noise Ratio (SNR) is so low that a Signal waveform is buried in Noise, direct observation of the waveform cannot determine whether the weak Signal exists, and thus detection by a special method is required. The detection of periodic weak signals is widely applied in many fields such as communication, mechanical flaw detection, neurobiology and the like.
A simple and effective detection method is digital summation, which samples the signal by an ADC (Analog-to-digital converter), the sampling rate of which is exactly an integer multiple of the repetition frequency of the weak signal to be detected. The signal-to-noise ratio of the weak signal can be improved by performing corresponding sampling point accumulation on the signal waveforms of a plurality of repetition periods, and when the accumulation times are enough, the accumulation sum corresponding to the weak signal is obviously different from the accumulation sum corresponding to the noise, so that the existence of the weak signal can be detected. This method is reported in a paper by GERHARD SCHMIDT et al (comparative code and Digital filtration for Detection of Weak VHF radio Signals from the messenger, 1979).
Early ADCs were clocked by the same clock as the data clock and the sampling clock. With the continuous improvement of the sampling rate of the ADC, some types of ADCs are available, the sampling clock frequency of which is even times of the data clock frequency, and this design can reduce the difficulty of transmitting the sampling data of the ADC to the back end, for example: ADS5400 chips from TEXAS INSTRUMENTENTS. However, in this design, since the internal circuit of the ADC partially operates at a clock frequency different from the sampling rate, a periodic weak interference signal having a period that is an even multiple of the sampling period of the ADC is mixed in the sampling data of the ADC. Since the weak interference signal is generated by the internal circuit of the ADC, it cannot be eliminated by the analog filter circuit before the ADC. When the signal-to-noise ratio of the weak interference signal cannot be considered to be much smaller than that of the periodic weak signal to be detected, the presence of the weak interference signal may seriously affect the detection result of the digital summation method, and may even cause the digital summation method to fail.
Disclosure of Invention
The invention aims to provide a periodic weak signal detection method and device based on pseudo median accumulation, so as to eliminate the influence of weak interference signals with even-numbered times of sampling periods on periodic weak signal detection.
The purpose of the invention is realized by the following technical scheme:
a periodic weak signal detection method based on pseudo median accumulation comprises the following steps:
sampling an analog signal possibly having a periodic weak signal by using an ADC (analog to digital converter) to obtain sampling data, wherein the sampling rate of the ADC is N times of the repetition frequency of the periodic weak signal, N is 4P, P is a positive integer, the number of the sampling data is N ×L + P, and L is a positive integer;
outputting the sampling data into two paths according to the serial number to obtain two groups of sampling data, wherein P data delay exists between the two groups of sampling data, each group of sampling data is divided into L sections, the number of each section of sampling data is 4P, and the two groups of data are partially overlapped;
comparing the maximum value of the left difference and the right difference with a set threshold value; if the maximum value of the left difference and the right difference is larger than the threshold value, the existence of a periodic weak signal is determined, and the signal-to-noise ratio is calculated according to the maximum value of the left difference and the right difference; otherwise, the periodic weak signal is deemed to be absent.
A periodic weak signal detection device based on pseudo-median accumulation, comprising: an ADC and a digital detection unit; wherein:
the ADC is used for sampling an analog signal possibly having a periodic weak signal to obtain sampling data, wherein the sampling rate of the ADC is N times of the repetition frequency of the periodic weak signal, N is 4P, P is a positive integer, the number of the sampling data is N ×L + P, L is a positive integer, and the signal-to-noise ratio of the periodic weak signal is smaller than a set lowest index;
the digital detection unit comprises a data dividing and delaying unit, a left and right difference calculating unit, a two-input maximum value calculating unit and an over-threshold discriminating unit, wherein the data dividing and delaying unit is used for outputting sampling data into two paths according to serial numbers to obtain two groups of sampling data, P data delay exists between the two groups of sampling data, each group of sampling data is divided into L sections, the number of each section of sampling data is 4P, the two groups of data are partially overlapped, the left and right difference calculating unit calculates left and right pseudo-median of each section of sampling data through a pseudo-median extracting method, then the group is used as a unit to sum all left pseudo-median and right pseudo-median in the group, then the absolute value of the difference value of the sum result is calculated as left and right differences to obtain two left and right differences, the two-input maximum value calculating unit is used for selecting the maximum value in the left and right differences, the over-threshold discriminating unit is used for comparing the maximum value in the left and right differences with a set threshold value, if the maximum value in the left and right differences is greater than the threshold value, a periodic weak signal exists, and otherwise, the signal-signal is calculated through the maximum value in.
The technical scheme provided by the invention can be seen that the periodic weak signal can be detected from the noise and is not influenced by the periodic weak interference signal of even-numbered times of the sampling period introduced in the sampling process; moreover, the median is a statistic for resisting extreme value interference, so the method has better robustness. In addition, there is a potential feature of this scheme: since the maximum value of the left-right difference has a positive correlation with the signal-to-noise ratio of the periodic weak signal, the periodic weak signal with a determined shape can also be used to estimate the signal-to-noise ratio of the signal.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a flowchart of a periodic weak signal detection method based on pseudo-median accumulation according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a periodic weak signal detection apparatus based on pseudo-median accumulation according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a digital detection unit according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a left-right difference calculating unit according to an embodiment of the present invention;
fig. 5 is a schematic diagram of a K input median extraction unit according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention provides a periodic weak signal detection method based on pseudo median accumulation, as shown in fig. 1, which mainly comprises the following steps:
1. sampling an analog signal possibly having a periodic weak signal by using an ADC (analog to digital converter) to obtain sampling data, wherein the sampling rate of the ADC is N times of the repetition frequency of the periodic weak signal, N is 4P, P is a positive integer, the number of the sampling data is N ×L + P, L is a positive integer, and the signal-to-noise ratio of the periodic weak signal is smaller than a set lowest index.
In the embodiment of the invention, the analog signal can be filtered by the filter and then enters the ADC for sampling.
2. The method comprises the steps of outputting sampling data into two paths according to serial numbers to obtain two groups of sampling data, wherein P data delay exists between the two groups of sampling data, each group of sampling data is divided into L sections, the number of each section of sampling data is 4P, calculating left and right pseudo-median of each section of sampling data by a pseudo-median extraction method, summing all left pseudo-median and right pseudo-median in the group by taking the group as a unit, calculating the absolute value of the difference value of the summation result as left and right differences, and obtaining two left and right differences.
The preferred embodiment of this step is as follows:
the first group of sampling data is sampling data with serial numbers from 1 to N ×L, and the second group of sampling data is sampling data with serial numbers from P +1 to N ×L + P;
the left and right pseudo-median sequence calculated by the first group of sampling data is marked as ML[i]、MR[i](ii) a And recording left and right pseudo median sequences calculated by the second group of sampling data as M'L[i]、M'R[i]，i＝1,2,…,L；
For all ML[i]、MR[i]、M'L[i]And M'R[i]Respectively summing, and recording the summation result as: SUML、SUMR、SUM'LAnd SUM'R；
Then, the left-right difference D is calculatedLRAnd D'LRWherein D isLR＝|SUML-SUMR|，D'LR＝|SUM'L-SUM'R|。
Preferably, the method for calculating the left and right pseudo-medians of each segment of data by the pseudo-median extraction method includes:
the quantity of each segment of sampling Data is 4P, and the sampling Data with the serial number from 1 to 2P is used as DataLAnd the sampling Data with the serial number from 2P +1 to 4P is used as DataR；
For DataLUniformly dividing the data into 2P/K sections, wherein the data volume of each section is K, and each section is input into a median extraction unit through K to calculate a median so as to obtain a median sequence; wherein 2P ═ KAK is an even number, A is a positive integer;
if the length of the obtained median sequence is greater than 1, the median sequence is evenly divided into a plurality of sections, the data volume of each section is K, and each section is input into a median extraction unit through K to calculate the median, so that a new median sequence is obtained; repeating the steps until only one median exists in the median sequence, wherein the finally obtained median is the left pseudo median of the sample data;
for DataRAnd processing in the same way to obtain the right pseudo-median of the affiliated sampling data.
Preferably, the way of calculating the median by the K input median extracting unit includes:
the K input median extraction unit firstly sorts K input data according to numerical value to obtain an ordered sequence SD [ K ], K is 1,2, …, K, and then calculates the median M ═ SD [ K/2] + SD [ K/2+1 ]/2.
3. Comparing the maximum value of the left difference and the right difference with a set threshold value; if the maximum value of the left difference and the right difference is larger than the threshold value, the existence of a periodic weak signal is determined, and the signal-to-noise ratio is calculated according to the maximum value of the left difference and the right difference; otherwise, the periodic weak signal is deemed to be absent.
The scheme provided by the embodiment of the invention can detect the periodic weak signal from the noise and is not influenced by the periodic weak interference signal with even-numbered times of the sampling period introduced in the sampling process. The pseudo median is obtained by extracting the median step by step, and is easy to realize in software or hardware. For the periodic weak signal with determined shape, the method provided by the invention can also be used for estimating the signal-to-noise ratio of the periodic weak signal. In addition, the median is a statistic for resisting extreme value interference, so the method provided by the invention has better robustness.
For ease of understanding, the following description is made with reference to a specific example.
In this example, a positive periodic weak pulse signal may be superimposed on the signal to be measured on the basis of gaussian noise; when the signal to be measured is Gaussian noise and periodic weak pulse, the signal to be measured is a periodic weak signal, and the signal-to-noise ratio of the signal to be measured needs to be estimated; when the signal to be measured is gaussian noise, the signal to be measured is not a periodic weak signal.
Let us say the standard deviation of Gaussian noise as σ0And the amplitude of the pulse signal is S, the signal-to-noise ratio of the pulse signal is defined as:
SNR(dB)＝＝20log1o(S/σo)
in this example, the resolution of the ADC is 1bit, when the signal amplitude is greater than 0V, the output code value is 1, when the signal amplitude is less than or equal to 0V, the output code value is 0, when the signal amplitude is less than or equal to 0V, the sampling rate of the ADC is N128 times the repetition frequency of the weak pulse signal to be measured, corresponding to P32, K4, a 3, L is 10000, and therefore, the number of the sampling data is (N ×L + P) 1280032.
After sampling data are obtained, sequentially dividing the sampling data with the serial numbers ranging from 1 to 1280000 into 10000 sections, wherein the data volume of each section is 128, and each section calculates a pseudo median M through a pseudo median extraction methodL[i]、MR[i]I ═ 1,2, …, 10000; sequentially dividing sampling data with serial numbers of 33-1280032 into 10000 sections, wherein the data volume of each section is 128, and each section calculates a pseudo median M 'by a pseudo median extraction method'L[i]、M'R[i]，i＝1,2,…,10000。
Then, for all ML[i]SUM to get SUMLFor all MR[i]SUM to get SUMRTo all of M'L[i]Summation to give SUM'LTo all of M'R[i]Summation to give SUM'R。
Then, a left-right difference D of the pseudo median accumulated sum is calculatedLRAnd D'LRWherein D isLR＝|SUML-SUMR|，D'LR＝|SUM'L-SUM'R|。
Next, max _ D is calculated, where max _ D is DLRAnd D'LRMaximum value of (1);
finally, comparing max _ D with a threshold value TH, and if max _ D is greater than TH, determining that the periodic weak signal exists; otherwise, the periodic weak signal is deemed to be absent. Wherein the value of TH is determined by preliminary calibration.
The pseudo-median extraction method used in the above process includes the steps of:
s'1, for 128 sampling Data, using the sampling Data with serial numbers from 1 to 64 as DataLAnd using the sampling Data with serial numbers from 65 to 128 as DataR。
S'2, for DataLThe data size of each segment is 4, and each segment calculates the median through a 4-input median extraction unit, so that a median sequence with the length of 16 is obtained.
S'3, because the length of the median sequence obtained in the last step is greater than 1, the median sequence is evenly divided into 4 sections, the data volume of each section is 4, and each section is input into a median extraction unit through 4 to calculate the median, so that a new median sequence with the length of 4 is obtained. The 4 medians in the new sequence are calculated by the 4-input median extraction unit to obtain DataLCorresponding pseudo-median ML。
S'4, for DataRSimilar to DataLObtaining the corresponding pseudo-median M by the method of S '2 and S'3R。
The function of the 4-input median extraction unit used in the above process is: the 4 input data are sorted according to the value size to obtain an ordered sequence SD [ k ], wherein k is 1,2,3,4, and the unit outputs a median M ═ SD [2] + SD [3 ])/2.
A monte carlo simulation was performed on this example: when a periodic weak pulse signal with positive polarity exists, max _ D obtained by 5 times of simulation is 100.8750, 81.2500, 105.7500, 122.0000 and 79.6250; when the positive periodic weak pulse signal is absent, max _ D obtained by 5 simulations is 23.3750, 27.2500, 13.0000, 28.1250 and 15.3750 respectively. Monte Carlo simulation results show the effectiveness of the periodic weak signal detection method based on pseudo-median accumulation provided by the invention.
Another embodiment of the present invention further provides a device for detecting a periodic weak signal based on pseudo-median accumulation, which can be used to implement the foregoing method, as shown in fig. 2, the device mainly includes: an ADC and a digital detection unit; wherein:
the ADC is used for sampling an analog signal possibly having a periodic weak signal to obtain sampling data, the sampling rate of the ADC is N times of the repetition frequency of the periodic weak signal, N is 4P, P is a positive integer, the number of the sampling data is N ×L + P, L is a positive integer, the signal-to-noise ratio of the periodic weak signal is smaller than a set lowest index, and in the embodiment of the invention, the analog signal can be filtered through a filter and then enters the ADC for sampling.
Illustratively, the resolution of the ADC may be set to 8 bits, and the sampling rate of the ADC is 32 times the repetition frequency of the periodic weak signal.
As shown in FIG. 3, the digital detection unit comprises a data dividing and delaying unit, a left-right difference calculating unit, a two-input maximum value calculating unit and an over-threshold discriminating unit, wherein the data dividing and delaying unit is used for outputting sampling data into two paths according to serial numbers to obtain two groups of sampling data, P (for example, P is 8) data delay exists between the two groups of sampling data, each group of sampling data is divided into L sections, the number of each section of sampling data is 4P, the left-right difference calculating unit calculates left-right pseudo-median of each section of sampling data by a pseudo-median extracting method, then the group is used as a unit to sum all left-pseudo-median and right-pseudo-median in the group respectively, and then the absolute value of the difference of the sum result is calculated as left-right difference to obtain two left-right differences, the number of the left-right difference calculating unit is two, each left-right difference calculating unit independently calculates left-right difference of one group of sampling data, the two-input maximum value calculating units are used for selecting the maximum value in the left-right difference, the over-threshold discriminating unit is used for comparing the maximum value of the left-right difference with a set threshold, if the signal-right difference is larger than the maximum value, the weak signal period, and the maximum value is judged if the signal.
As shown in fig. 4, each of the left-right difference calculation units includes: a chain K input median extraction units (fig. 4 takes a chain 4 input median extraction unit as an example), two digital accumulation units, a subtraction unit and an absolute value calculation unit; the A chain type K input median extraction units are connected in cascade, data output by the last chain type K input median extraction unit are alternately input into the two digital accumulation units for accumulation, the two accumulation results are input into the subtraction unit for difference calculation, and the difference result is input into the absolute value calculation unit for calculation to obtain the left-right difference of the pseudo median accumulation sum; wherein:
the first group of sampling data is sampling data with serial numbers from 1 to N ×L, and the second group of sampling data is sampling data with serial numbers from P +1 to N ×L + P;
a chain K input median extracting units in the first left-right difference computing unit output left-right pseudo median sequences M of the first group of sampling dataL[i]、MR[i](ii) a A chain K input median extracting units in the second left-right difference calculating unit output left-right pseudo median sequences M 'of the second group of sampling data'L[i]、M'R[i]，i＝1,2,…,L；
Two digital accumulation units in the first left-right difference calculation unit pair all ML[i]、MR[i]Respectively summing, and marking as UM corresponding to the summation resultL、SUMR(ii) a Two digital accumulation units in the second left-right difference calculation unit pair all M'L[i]、M'R[i]Respectively summing, and recording the summation result as: SUM'L、SUM'R；
The subtraction unit in the first left-right difference calculation unit cooperates with the absolute value calculation unit to calculate the left-right difference DLR：DLR＝|SUML-SUMRL, |; the subtraction unit in the second left-right difference calculation unit calculates the left-right difference D 'in cooperation with the absolute value calculation unit'LR：D'LR＝|SUM'L-SUM'R|。
Preferably, the method for calculating the left and right pseudo-medians of each segment of data by the pseudo-median extraction method includes:
each segment being formed ofThe number of the sampling Data is 4P, and the sampling Data with the serial number from 1 to 2P is used as DataLAnd the sampling Data with the serial number from 2P +1 to 4P is used as DataR；
For DataLUniformly dividing the data into 2P/K sections, wherein the data volume of each section is K, and each section is input into a median extraction unit through K to calculate a median so as to obtain a median sequence; wherein 2P ═ KAK is an even number, A is a positive integer;
if the length of the obtained median sequence is greater than 1, the median sequence is evenly divided into a plurality of sections, the data volume of each section is K, and each section is input into a median extraction unit through K to calculate the median, so that a new median sequence is obtained; repeating the steps until only one median exists in the median sequence, wherein the finally obtained median is the left pseudo median of the sample data;
for DataRAnd processing in the same way to obtain the right pseudo-median of the affiliated sampling data.
As shown in fig. 5, the K input median extracting unit includes: the device comprises a serial-parallel conversion unit, a sorting unit and an average value calculation unit;
the serial-parallel conversion unit is used for correspondingly storing the K input data into K storage units;
the sorting unit is used for sorting K input data according to the numerical value to obtain an ordered sequence SD [ K ], wherein K is 1,2, … and K;
and an average value calculation unit for calculating the median M ═ (SD [ K/2] + SD [ K/2+1 ])/2.
For the technical details related to the above-mentioned apparatus, reference may be made to the foregoing method embodiments, and thus, the detailed description is omitted. It should be noted that in the above different embodiments, one or more specific numerical values are given for each parameter, but the given specific numerical values are only examples and are not limiting, and in actual operation, a user may set the specific numerical values of each parameter according to actual situations or experience.
It will be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to perform all or part of the above described functions.
Through the above description of the embodiments, it is clear to those skilled in the art that the above embodiments can be implemented by software, and can also be implemented by software plus a necessary general hardware platform. With this understanding, the technical solutions of the embodiments can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.), and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods according to the embodiments of the present invention.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. A periodic weak signal detection method based on pseudo median accumulation is characterized by comprising the following steps:
sampling an analog signal possibly having a periodic weak signal by using an ADC (analog to digital converter) to obtain sampling data, wherein the sampling rate of the ADC is N times of the repetition frequency of the periodic weak signal, N is 4P, P is a positive integer, the number of the sampling data is N ×L + P, and L is a positive integer;
outputting the sampling data into two paths according to the serial number to obtain two groups of sampling data, wherein P data delay exists between the two groups of sampling data, each group of sampling data is divided into L sections, the number of each section of sampling data is 4P, and the two groups of data are partially overlapped;
comparing the maximum value of the left difference and the right difference with a set threshold value; if the maximum value of the left difference and the right difference is larger than the threshold value, the existence of a periodic weak signal is determined, and the signal-to-noise ratio is calculated according to the maximum value of the left difference and the right difference; otherwise, the periodic weak signal is deemed to be absent.
2. The method for detecting the periodic weak signal based on the pseudo-median accumulation according to claim 1, wherein the method comprises the steps of dividing all sampling data into two groups according to serial numbers, dividing each group into L sections, calculating left and right pseudo-medias of each section of the sampling data by a pseudo-median extraction method, respectively summing all left pseudo-medias and right pseudo-medias in the group by taking the group as a unit, and calculating an absolute value of a difference value of a summation result to serve as a left and right difference so as to obtain two left and right differences, wherein the number of the left and right differences comprises:
the first group of sampling data is sampling data with serial numbers from 1 to N ×L, and the second group of sampling data is sampling data with serial numbers from P +1 to N ×L + P;
the left and right pseudo-median sequence calculated by the first group of sampling data is marked as ML[i]、MR[i](ii) a And recording left and right pseudo median sequences calculated by the second group of sampling data as M'L[i]、M'R[i]，i＝1,2,…,L；
For all ML[i]、MR[i]、M'L[i]And M'R[i]Respectively summing, and recording the summation result as: SUML、SUMR、SUM'LAnd SUM'R；
Then, the left-right difference D is calculatedLRAnd D'LRWherein D isLR＝|SUML-SUMR|，D'LR＝|SUM'L-SUM'R|。
3. The method for detecting periodic weak signals based on pseudo-median accumulation according to claim 1 or 2, wherein the way of calculating the left and right pseudo-median of each segment of data by the pseudo-median extraction method comprises:
the quantity of each segment of sampling Data is 4P, and the sampling Data with the serial number from 1 to 2P is used as DataLAnd the sampling Data with the serial number from 2P +1 to 4P is used as DataR；
For DataLUniformly dividing the data into 2P/K sections, wherein the data volume of each section is K, and each section is input into a median extraction unit through K to calculate a median so as to obtain a median sequence; wherein 2P ═ KAK is an even number, A is a positive integer;
if the length of the obtained median sequence is greater than 1, the median sequence is evenly divided into a plurality of sections, the data volume of each section is K, and each section is input into a median extraction unit through K to calculate the median, so that a new median sequence is obtained; repeating the steps until only one median exists in the median sequence, wherein the finally obtained median is the left pseudo median of the sample data;
for DataRAnd processing in the same way to obtain the right pseudo-median of the affiliated sampling data.
4. The method as claimed in claim 3, wherein the calculating the median by the K input median extracting unit comprises:
the K input median extraction unit firstly sorts K input data according to numerical value to obtain an ordered sequence SD [ K ], K is 1,2, …, K, and then calculates the median M ═ SD [ K/2] + SD [ K/2+1 ]/2.
5. A periodic weak signal detection device based on pseudo-median accumulation, comprising: an ADC and a digital detection unit; wherein:
the ADC is used for sampling an analog signal possibly having a periodic weak signal to obtain sampling data, wherein the sampling rate of the ADC is N times of the repetition frequency of the periodic weak signal, N is 4P, P is a positive integer, the number of the sampling data is N ×L + P, L is a positive integer, and the signal-to-noise ratio of the periodic weak signal is smaller than a set lowest index;
the digital detection unit comprises a data dividing and delaying unit, a left and right difference calculating unit, a two-input maximum value calculating unit and an over-threshold discriminating unit, wherein the data dividing and delaying unit is used for outputting sampling data into two paths according to serial numbers to obtain two groups of sampling data, P data delay exists between the two groups of sampling data, each group of sampling data is divided into L sections, the number of each section of sampling data is 4P, the two groups of data are partially overlapped, the left and right difference calculating unit calculates left and right pseudo-median of each section of sampling data through a pseudo-median extracting method, then the group is used as a unit to sum all left pseudo-median and right pseudo-median in the group, then the absolute value of the difference value of the sum result is calculated as left and right differences to obtain two left and right differences, the two-input maximum value calculating unit is used for selecting the maximum value in the left and right differences, the over-threshold discriminating unit is used for comparing the maximum value in the left and right differences with a set threshold value, if the maximum value in the left and right differences is greater than the threshold value, a periodic weak signal exists, and otherwise, the signal-signal is calculated through the maximum value in.
6. The apparatus according to claim 5, wherein the number of the left and right difference calculating units is two, and each of the left and right difference calculating units independently calculates the left and right differences of a set of the sampled data; each of the left-right difference calculation units includes: a chain K input median extraction units, two digital accumulation units, a subtraction unit and an absolute value calculation unit; the A chain type K input median extraction units are connected in cascade, data output by the last chain type K input median extraction unit are alternately input into the two digital accumulation units for accumulation, the two accumulation results are input into the subtraction unit for difference calculation, and the difference result is input into the absolute value calculation unit for calculation to obtain the left-right difference of the pseudo median accumulation sum; wherein:
the first group of sampling data is sampling data with serial numbers from 1 to N ×L, and the second group of sampling data is sampling data with serial numbers from P +1 to N ×L + P;
a chain K input median extracting units in the first left-right difference computing unit output left-right pseudo median sequences M of the first group of sampling dataL[i]、MR[i](ii) a A chain K input median extracting units in the second left-right difference calculating unit output left-right pseudo median sequences M 'of the second group of sampling data'L[i]、M'R[i]，i＝1,2,…,L；
Two digital accumulation units in the first left-right difference calculation unit pair all ML[i]、MR[i]Respectively summing, and marking as UM corresponding to the summation resultL、SUMR(ii) a Two digital accumulation units in the second left-right difference calculation unit pair all M'L[i]、M'R[i]Respectively summing, and recording the summation result as: SUM'L、SUM'R；
The subtraction unit in the first left-right difference calculation unit cooperates with the absolute value calculation unit to calculate the left-right difference DLR：DLR＝|SUML-SUMRL, |; the subtraction unit in the second left-right difference calculation unit calculates the left-right difference D 'in cooperation with the absolute value calculation unit'LR：D'LR＝|SUM'L-SUM'R|。
7. The apparatus according to claim 5 or 6, wherein the method for calculating the left and right pseudo-medians of each segment of data by the pseudo-median extraction method comprises:
the quantity of each segment of sampling Data is 4P, and the sampling Data with the serial number from 1 to 2P is used as DataLAnd the sampling Data with the serial number from 2P +1 to 4P is used as DataR；
For DataLUniformly dividing the data into 2P/K segments, wherein the data amount of each segment is K, and each segment is input into a median extraction unit through KCalculating a median to obtain a median sequence; wherein 2P ═ KAK is an even number, A is a positive integer;
if the length of the obtained median sequence is greater than 1, the median sequence is evenly divided into a plurality of sections, the data volume of each section is K, and each section is input into a median extraction unit through K to calculate the median, so that a new median sequence is obtained; repeating the steps until only one median exists in the median sequence, wherein the finally obtained median is the left pseudo median of the sample data;
for DataRAnd processing in the same way to obtain the right pseudo-median of the affiliated sampling data.
8. The apparatus of claim 7, wherein the K input median extracting unit comprises: the device comprises a serial-parallel conversion unit, a sorting unit and an average value calculation unit;
the serial-parallel conversion unit is used for correspondingly storing the K input data into K storage units;
the sorting unit is used for sorting K input data according to the numerical value to obtain an ordered sequence SD [ K ], wherein K is 1,2, … and K;
and an average value calculation unit for calculating the median M ═ (SD [ K/2] + SD [ K/2+1 ])/2.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010295524.3A CN111490789B (en) | 2020-04-15 | 2020-04-15 | Periodic weak signal detection method and device based on pseudo median accumulation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010295524.3A CN111490789B (en) | 2020-04-15 | 2020-04-15 | Periodic weak signal detection method and device based on pseudo median accumulation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111490789A true CN111490789A (en) | 2020-08-04 |
| CN111490789B CN111490789B (en) | 2023-03-10 |
Family
ID=71796180
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010295524.3A Active CN111490789B (en) | 2020-04-15 | 2020-04-15 | Periodic weak signal detection method and device based on pseudo median accumulation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111490789B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112511165A (en) * | 2020-11-25 | 2021-03-16 | 中国科学技术大学 | Multi-target weak signal detection method and device based on single-bit sampling |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002221546A (en) * | 2001-01-26 | 2002-08-09 | Nippon Telegr & Teleph Corp <Ntt> | Time periodic feeble signal detection method in noise, its device, its program and its recording medium |
| JP2006054533A (en) * | 2004-08-10 | 2006-02-23 | Nec Corp | Periodicity detection method and periodicity detecting apparatus for periodic signal |
| WO2007009558A1 (en) * | 2005-07-22 | 2007-01-25 | Institute Of Electronics And Computer Sciences Of Latvian University | Method and apparatus for spectral estimations adapted to non-uniformities of sampling |
| JP2008286736A (en) * | 2007-05-21 | 2008-11-27 | Nippon Sheet Glass Co Ltd | Method and apparatus for detecting feeble signal |
| US20090196389A1 (en) * | 2008-01-31 | 2009-08-06 | Nec Electronics Corporation | Signal processing method and circuit to convert analog signal to digital signal |
| CN103884421A (en) * | 2014-03-24 | 2014-06-25 | 重庆邮电大学 | Duffing oscillator weak-signal detection method based on united denoising and pseudo Hamiltonian |
| CN103913222A (en) * | 2014-04-25 | 2014-07-09 | 重庆邮电大学 | Duffing oscillator weak signal time domain detection method based on phase-locked loop |
| CN106772268A (en) * | 2016-12-27 | 2017-05-31 | 哈尔滨工业大学 | A kind of weak signal blind checking method under white Gaussian noise |
| WO2018035719A1 (en) * | 2016-08-23 | 2018-03-01 | 华为技术有限公司 | Method for acquiring phase discrimination signal in clock recovery circuit and phase discriminator |
| CN107991695A (en) * | 2017-11-07 | 2018-05-04 | 南京航空航天大学 | Big Dipper weak signal catching method based on zero padding algorithm and differential coherence algorithm |
| CN108957120A (en) * | 2018-05-17 | 2018-12-07 | 北华航天工业学院 | A kind of weak signal extraction and system |
-
2020
- 2020-04-15 CN CN202010295524.3A patent/CN111490789B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002221546A (en) * | 2001-01-26 | 2002-08-09 | Nippon Telegr & Teleph Corp <Ntt> | Time periodic feeble signal detection method in noise, its device, its program and its recording medium |
| JP2006054533A (en) * | 2004-08-10 | 2006-02-23 | Nec Corp | Periodicity detection method and periodicity detecting apparatus for periodic signal |
| WO2007009558A1 (en) * | 2005-07-22 | 2007-01-25 | Institute Of Electronics And Computer Sciences Of Latvian University | Method and apparatus for spectral estimations adapted to non-uniformities of sampling |
| JP2008286736A (en) * | 2007-05-21 | 2008-11-27 | Nippon Sheet Glass Co Ltd | Method and apparatus for detecting feeble signal |
| US20090196389A1 (en) * | 2008-01-31 | 2009-08-06 | Nec Electronics Corporation | Signal processing method and circuit to convert analog signal to digital signal |
| CN103884421A (en) * | 2014-03-24 | 2014-06-25 | 重庆邮电大学 | Duffing oscillator weak-signal detection method based on united denoising and pseudo Hamiltonian |
| CN103913222A (en) * | 2014-04-25 | 2014-07-09 | 重庆邮电大学 | Duffing oscillator weak signal time domain detection method based on phase-locked loop |
| WO2018035719A1 (en) * | 2016-08-23 | 2018-03-01 | 华为技术有限公司 | Method for acquiring phase discrimination signal in clock recovery circuit and phase discriminator |
| CN106772268A (en) * | 2016-12-27 | 2017-05-31 | 哈尔滨工业大学 | A kind of weak signal blind checking method under white Gaussian noise |
| CN107991695A (en) * | 2017-11-07 | 2018-05-04 | 南京航空航天大学 | Big Dipper weak signal catching method based on zero padding algorithm and differential coherence algorithm |
| CN108957120A (en) * | 2018-05-17 | 2018-12-07 | 北华航天工业学院 | A kind of weak signal extraction and system |
Non-Patent Citations (3)
| Title |
|---|
| DOMINIQUE PASTOR等: ""Robust Estimation of Noise Standard Deviation in Presence of Signals With Unknown Distributions and Occurrences"", 《IEEE TRANSACTIONS ON SIGNAL PROCESSING》 * |
| ZHONGTAO SHEN等: ""Study on the Real-Time Lossless Data Compression Method Used in the Readout System for Micropattern Gas Detector"", 《IEEE TRANSACTIONS ON NUCLEAR SCIENCE》 * |
| 仝海波: ""卫星导航信号联合处理技术研究"", 《中国博士学位论文全文数据库•信息科技辑》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112511165A (en) * | 2020-11-25 | 2021-03-16 | 中国科学技术大学 | Multi-target weak signal detection method and device based on single-bit sampling |
| CN112511165B (en) * | 2020-11-25 | 2023-11-28 | 中国科学技术大学 | Multi-target weak signal detection method and device based on single-bit sampling |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111490789B (en) | 2023-03-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP4723030B2 (en) | Improved digital trigger circuit | |
| US9191260B1 (en) | Method and apparatus to determine a match between signals | |
| US7860688B2 (en) | Signal baseline processing device and processing method thereof | |
| US7254168B2 (en) | Method for decomposing timing jitter on arbitrary serial data sequences | |
| WO2012088781A1 (en) | Method and system for digitized pileup waveform processing | |
| EP3070847B1 (en) | Method and device for acquiring time point where glimmering pulse passes over threshold | |
| CN111490789B (en) | Periodic weak signal detection method and device based on pseudo median accumulation | |
| CN104101751A (en) | Information entropy-based digital storage oscilloscope vertical resolution improving method | |
| CN108491318A (en) | A kind of sequence detecting method, electronic equipment and storage medium | |
| CN117111016B (en) | Real-time pulse analysis method and system based on channelization in complex electromagnetic environment | |
| CN114236594A (en) | Nuclear pulse signal digital triangle-trapezoid two-channel forming method | |
| US7248982B1 (en) | Finding data dependent jitter with a DDJ calculator configured by regression | |
| US20060093027A1 (en) | Method of finding data dependent timing and voltage jitter for different bits in an arbitrary digital signal in accordance with selected surrounding bits | |
| CN110632563B (en) | Intra-pulse frequency coding signal parameter measuring method based on short-time Fourier transform | |
| CN106802293A (en) | waveform peak detection method and device | |
| CN110595529B (en) | Method for rapidly detecting weak periodic signals under strong background noise | |
| CN109948223B (en) | Pulse amplitude acquisition method based on Lagrange interpolation | |
| KR101035295B1 (en) | Method of classifying a series of pulses using probability distribution | |
| RU2525302C1 (en) | Method for automatic detection of narrow-band signals (versions) | |
| JP3097034B1 (en) | Signal analyzer | |
| KR102109839B1 (en) | A receiver for receiving a navigation signal and a method for measuring the navigation signal thereof | |
| WO2008060670A2 (en) | Low noise voltage-to-frequency conversion apparatus and method for quantum measurements | |
| JP2024034324A (en) | Real number expansion information processing device and method | |
| CN115796095A (en) | Pulse interpolation timing parameter optimization method based on genetic algorithm | |
| Lin et al. | Performance analysis of digital wideband receiver based on reconstruction of compressed sensing data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |