CN114624512A - Frequency modulation signal inverse triangle noise suppression and frequency measurement method - Google Patents
Frequency modulation signal inverse triangle noise suppression and frequency measurement method Download PDFInfo
- Publication number
- CN114624512A CN114624512A CN202210283593.1A CN202210283593A CN114624512A CN 114624512 A CN114624512 A CN 114624512A CN 202210283593 A CN202210283593 A CN 202210283593A CN 114624512 A CN114624512 A CN 114624512A
- Authority
- CN
- China
- Prior art keywords
- signal
- variable
- value
- frequency
- array
- 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.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R23/00—Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
- G01R23/02—Arrangements for measuring frequency, e.g. pulse repetition rate; Arrangements for measuring period of current or voltage
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R23/00—Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
- G01R23/16—Spectrum analysis; Fourier analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Mathematical Physics (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Computational Mathematics (AREA)
- Pure & Applied Mathematics (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Algebra (AREA)
- Measuring Frequencies, Analyzing Spectra (AREA)
Abstract
A frequency modulation signal inverse triangle noise suppression and frequency measurement method relates to the electronic technical field of communication control and the like, solves the problems of large calculated amount, low measurement speed and the like caused by the fact that the existing Fourier method needs to calculate all possible frequency components and then carries out sequencing search, and particularly provides a measurement method capable of processing a signal mixed with noise; the high-precision frequency is realized by five steps of measuring the amplitude of a noise suppression signal, obtaining a signal triangular interval for calculation, carrying out inverse triangular transformation, calculating the signal frequency and calculating the average frequency. For the mixed signal after digital quantization, firstly calculating the noise suppression amplitude, then carrying out reverse triangulation calculation in a triangulation calculation interval to obtain the instantaneous frequency in the interval, finally calculating the average frequency of all the intervals, measuring the frequency of the signal component with the maximum intensity, and the calculation amount is obviously lower than that of the traditional Fourier mode.
Description
Technical Field
The invention relates to the technical field of electronics such as communication control, in particular to an anti-triangular noise suppression and frequency measurement method for a frequency modulation signal.
Background
In the field of electronic technologies such as communication control, the frequency of an electronic signal often needs to be measured; measuring the frequency of a high-frequency signal in a mode of counting pulses of a signal point to be characterized within a fixed time length, measuring a time length measuring period in which the signal point to be characterized repeatedly appears, and obtaining a measuring period mode of the frequency by taking the reciprocal; after the signal is superimposed with noise, the point to be characterized is interfered, so that the measurement precision is obviously reduced; when the signal-to-noise ratio is poor, if the frequency band of the signal is known, although the out-of-band noise can be suppressed by using a filter to improve the signal-to-noise ratio, for the in-band noise which cannot be suppressed by filtering, the method of searching the maximum component after analyzing various frequency components of the signal after Fourier expansion can be used for measurement; the Fourier method needs to calculate all possible frequency components first and then search in sequence, so that the calculation amount is large, the measurement speed is low, and the like.
Disclosure of Invention
The invention provides an inverse triangle noise suppression frequency measurement demodulation method for a frequency modulation signal, which aims to solve the problems of large calculation amount, low measurement speed and the like caused by the fact that all possible frequency components need to be calculated and then sequenced and searched in the existing Fourier method.
The method is realized by a frequency modulation signal inverse triangle noise suppression and frequency measurement system, wherein the frequency measurement system comprises a data input end, a memory, a processor and an output end;
the data input end inputs a signal to be tested and stores the signal in the memory;
the memory stores the signal to be tested obtained from the data input end; continuously storing N data logically in each measurement process to form a data structure of a one-dimensional array, which is expressed by Si;
the processor analyzes the data stored in the memory, calculates the triangular interval of the signal to be measured by measuring the amplitude of the noise suppression signal, performs inverse triangular transformation, calculates the frequency of the signal to be measured and calculates the average frequency of the signal to be measured, and obtains the instantaneous frequency f at the position where the index sequence number of the subscript is equal to P; the specific process is as follows:
firstly, measuring the amplitude of a noise suppression signal to obtain the instantaneous amplitude A of a signal to be detected after noise suppression is calculated; secondly, calculating the triangular interval of the signal to be measured, and storing the triangular interval in a variable D and a variable U, wherein the method comprises the following specific steps:
step a1, obtaining data S [ P ] with sequence number i-P position in the array S [ i ];
step A2, using variable K as cycle index sequence number, the initial value of K is equal to P;
step A3, comparing the size of S [ K ] and S [ K-1], if S [ K-1] is larger than S [ K ], executing step A4, otherwise, executing step A5;
step A3 is executed after step a4, K ═ K-1;
step A5, if the value of the variable K is less than P, the variable U is used for saving the value of K at the moment, then the step A6 is executed, otherwise, the step A12 is executed;
step A6, setting the initial value of a variable K equal to P;
step A7, comparing the S [ K ] and S [ K +1], if S [ K +1] is less than S [ K ], executing step A8, otherwise, executing step A9 by a failed jump;
step A8, after adding 1 to the variable K, executing step A7;
step A9, if the value of the variable K is larger than P, the variable D is used for storing the value of K at the moment, then the step A10 is executed, otherwise, the step A12 is executed in failure;
step A10, respectively adopting the numerical value in the variable U, subtracting 1 from the numerical value in U, and adding 1 to the numerical value in U as an index number, obtaining data from the array S to obtain the S [ U ], S [ U-1], and S [ U +1], if the numerical value obtained by subtracting S [ U-1] from S [ U ] is larger than the numerical value obtained by subtracting S [ U +1] from S [ U ], adding 1 to the variable U;
step A11, respectively using the numerical value in the variable D, subtracting 1 from the numerical value in D, and adding 1 to the numerical value in D as an index number, obtaining data from the array S to obtain SD, SD-1, and SD +1, if the numerical value of subtracting SD +1 from SD is larger than the numerical value of subtracting S-1 from SD, subtracting 1 from the variable D; at this time, the variable U and the variable D store the triangular interval information of the signal to be detected, and the step B1 is executed;
the initial value of the step A12 and the step K is equal to P;
step A13, comparing the S [ K ] and the S [ K +1], if the S [ K +1] is larger than the S [ K ], executing step A14, otherwise, skipping to execute step A15;
step a14, K + K, execute step a 13;
step A15, adopting a variable U to store the K value at the moment;
the initial value of the step A16 and K is equal to P;
step A17, comparing S [ K ] with S [ K-1], if S [ K-1] is less than S [ K ], executing step A18, otherwise, executing step A19;
step a17 is executed after step a18, K ═ K-1;
step A19, storing the K value at the moment by adopting a variable D;
step A20, respectively adopting the numerical value in the variable U, subtracting 1 from the numerical value in U, and adding 1 to the numerical value in U as an index number, obtaining data from the array S to obtain S [ U ], S [ U-1], and S [ U +1], if the difference of subtracting S [ U-1] from S [ U ] is less than the difference of subtracting S [ U +1] from S [ U ], then changing U to U-1;
step A21, respectively using the numerical value in the variable D, the numerical value in D minus 1 and the numerical value in D plus 1 as index numbers, obtaining data from the array S, obtaining S [ D ], S [ D-1] and S [ D +1], if the difference between S [ D ] and S [ D +1] is smaller than the difference between S [ D ] and S [ D-1], then D is D-1; at this time, the triangle interval information of the signal to be detected is stored in the variable U and the variable D, and the step B1 is executed;
then, carrying out inverse triangle transformation on the signal to be detected, and the specific process is as follows:
b1, defining a one-dimensional array Q, wherein the number of elements in the array is represented by Z, and the calculation method of Z is as follows;
Z=|U-D|
then defining a one-dimensional array R, wherein the number of elements in the array is also Z;
b2, defining a variable J to enable the value of J to be equal to U, then comparing the size of the variable U with that of the variable D, and enabling the variable J to be equal to the variable D if the variable U is larger than the variable D; and making the initial value of the variable K zero;
step B3, taking the variable J as the index sequence number of the array S, obtaining data S [ J ] from the array S, then calculating by using an inverse trigonometric function, and storing the obtained value into Q [ K ] taking K as the index sequence number in the array Q;
step B4, setting the value of R [ K ] with K as index sequence number in the array R equal to J; then, accumulating the variable J, comparing whether the variable J is smaller than Z after accumulating the variable K, if so, executing the step B3, otherwise, executing the step C1;
and finally, calculating the frequency of the signal to be detected, and specifically comprising the following steps:
c1, calculating the average value O of all elements in the array Q, and then calculating the average value B of all elements in the array R;
step C2, defining three variables G, X and Y, and setting the initial values to be zero;
step C3, obtaining data R [ G ] with G as an index sequence number in the array R, and subtracting the average value B to obtain a difference value W;
obtaining data Q [ G ] with G as an index sequence number in the array Q, and subtracting the average value O to obtain a difference value V;
multiplying the difference value W and the difference value V to obtain a product C;
increasing the value of variable X by C, i.e., X ═ X + C;
step C4, after the difference value W is squared, a squared value T is obtained; changing Y to Y + T;
step C5, changing the variable G to G +1, if the value of G is less than Z, returning to execute step C3, otherwise, calculating the instantaneous frequency f of the signal to be measured at the point P, which is input from the data input end;
and changing the point P to a position except the position obtained in the step A1, returning to the step A1 until all data intervals are calculated, calculating the average value of the instantaneous frequency f obtained from a plurality of data intervals, obtaining the average frequency of the signal to be measured, and outputting the average frequency from an output end.
The invention has the beneficial effects that: the frequency measurement method can process the measurement method mixed with noise signals; for the mixed signal after digital quantization, firstly calculating the noise suppression amplitude, then carrying out reverse triangulation calculation in a triangulation calculation interval to obtain the instantaneous frequency in the interval, finally calculating the average frequency of all the intervals, measuring the frequency of the signal component with the maximum intensity, and the calculation amount is obviously lower than that of the traditional Fourier mode.
According to the frequency measurement method, each frequency component does not need to be calculated, and in a mixed signal mixed with noise, the signal with the maximum intensity can be directly measured as long as the signal intensity is always greater than the noise; if the frequency measurement demodulation system is used for frequency modulation broadcasting, the anti-interference capability of a broadcasting receiving end can be improved.
Drawings
Fig. 1 is a schematic block diagram of an inverse triangle noise suppression frequency measurement method for a frequency modulation signal according to the present invention.
Detailed Description
Referring to fig. 1, the present embodiment is described, in which the method for inverse triangular noise suppression and frequency measurement of a frequency modulated signal is implemented by an inverse triangular noise suppression and frequency measurement system of a frequency modulated signal, the system including a data input terminal, a memory, a processor and an output terminal;
the signal to be measured is composed of an original signal and a superimposed noise signal and can have a direct current component; the original signal is a cosine signal with a single frequency, the frequency is represented by f, only the approximate range is known, and the precise value is not known; the instantaneous amplitude is also an unknown value, denoted by a; in the method of this embodiment, the objective is to accurately measure the frequency f of the original signal; f is lower than the upper limit of the highest frequency H; the amplitude of the original signal is greater than the amplitude of the noise signal;
the data input end inputs a signal to be detected, and if the signal to be detected is an analog signal, the signal to be detected needs to be converted by an analog-to-digital converter and then is sent to the data input end; requiring sampling an input signal to be tested at a fixed frequency F to obtain digital quantity data; the sampling frequency F must be ensured to be more than 8 times of the upper limit value H; the amplitude and the frequency of the signal to be measured are kept unchanged during a single measurement;
the memory stores the signal data to be tested obtained from the data input end; in each measurement process, N values of a batch of data are required and are stored logically and continuously to form a data structure of a one-dimensional array, which is represented by Si; wherein S is an array name, and i is a subscript index sequence number; the minimum value of the subscript index serial number i is zero, and the maximum value is N minus 1; defining the decreasing direction of the subscript index serial numbers as the left direction and the increasing direction of the subscript index serial numbers as the right direction;
the processor analyzes the data stored in the memory, obtains signal triangular interval calculation, inverse triangular transformation, signal frequency calculation and average frequency calculation by measuring the amplitude of the noise suppression signal, analyzes the instantaneous frequency with index number i equal to P and accurately measures the average frequency of the input signal to be measured.
Firstly, measuring the amplitude of a noise suppression signal;
in order to remove the direct current component of the signal in the array, the direct current voltage L in the signal needs to be calculated firstly;
then, subtracting the direct current voltage L from each element in the array S [ i ];
calculating the whole array by using the following formula to obtain a square mean root value M of the signal for the array Si after the direct current component is removed;
calculating the absolute average value E of the whole array by using the following formula;
substituting the signal root mean square value M and the absolute average value E into the following formula to calculate the signal amplitude A after noise suppression;
secondly, calculating a triangular interval of the signal to be measured;
the method comprises the following steps that a signal triangular interval is obtained, wherein the purpose of obtaining the signal triangular interval is to obtain the signal triangular interval stored in a variable D and a variable U;
a1, obtaining data S [ P ] with sequence number i ═ P in the array S [ i ];
a2, using a variable K as a cycle index sequence number, wherein the initial value of K is equal to P;
a3, comparing S [ K ] with S [ K-1], if S [ K-1] is larger than S [ K ], executing step A4, otherwise, jumping to execute step A5;
a4, executing step 3 after reducing the variable K by one;
a5, if the value of the variable K is less than P, the variable U is used for saving the value of K at the moment, and then the step A6 is executed, otherwise, the step A12 is executed;
a6, setting the initial value of a variable K equal to P;
a7, comparing S [ K ] with S [ K +1], if S [ K +1] is less than S [ K ], executing step 8, otherwise, executing step A9 by fail jump;
a8, executing the step A7 after adding one to the variable K;
a9, if the value of the variable K is larger than P, the step A10 is executed after the value of K at the moment is saved by the variable D, otherwise, the step A12 is executed in failure;
a10, respectively using the value in variable U, the value in U minus 1, and the value in U plus 1 as index numbers, obtaining data from the array S to obtain SU, SU-1, and SU +1, if the value obtained by subtracting SU-1 from SU is larger than the value obtained by subtracting SU +1 from SU, then adding 1 to variable U.
A11, respectively using the numerical value in the variable D, the numerical value in D minus 1 and the numerical value in D plus 1 as index numbers, obtaining data from the array S to obtain SD, SD-1 and SD +1, if the numerical value obtained by subtracting SD +1 from SD is larger than that obtained by subtracting SD-1 from SD, subtracting 1 from variable D; at the moment, the variable U and the variable D store the information of the signal triangular interval; step B1 is executed;
the initial value of A12, K is equal to P;
a13, comparing S [ K ] with S [ K +1], if S [ K +1] is larger than S [ K ], executing step A14, otherwise, executing step A15;
a14, adding 1 to the variable K and then executing the step 13;
a15, saving the K value at the moment by using a variable U;
the initial value of A16, K is equal to P;
a17, comparing S [ K ] with S [ K-1], if S [ K-1] is smaller than S [ K ], executing step A18, otherwise, jumping to execute step A19;
a18, after the variable K is reduced by 1, executing the step A17;
a19, storing the K value at the moment by using a variable D;
a20, respectively using the value in variable U, the value in U minus 1, and the value in U plus 1 as index numbers, obtaining data from the array S to obtain SU, SU-1, and SU +1, if the value obtained by subtracting SU-1 from SU is smaller than the value obtained by subtracting SU +1 from SU, then subtracting 1 from U.
A21, respectively using the numerical value in the variable D, the numerical value in D minus 1 and the numerical value in D plus 1 as index numbers, obtaining data from the array S to obtain SD, SD-1 and SD +1, if the numerical value obtained by subtracting SD +1 from SD is smaller than that obtained by subtracting SD-1 from SD, then subtracting 1 from variable D; at the moment, the variable U and the variable D store the information of the signal triangular interval; step B1 is executed;
thirdly, inverse triangle transformation; the method comprises the following specific steps of;
b1, defining a one-dimensional array Q, wherein the number of elements in the array is represented by Z, and the calculation method of Z is as follows;
Z=|U-D|
that is, Z is equal to the absolute value of the variable U minus the variable D;
defining a one-dimensional array R, wherein the number of elements in the array is also Z;
b2, defining a variable J, enabling the value of the J to be equal to U, then comparing the size of the variable U with that of the variable D, and enabling the variable J to be equal to the variable D if the variable U is larger than the variable D; and making the initial value of the variable K zero;
b3, taking the variable J as the index sequence number of the array S, obtaining data S [ J ] from the array S, then calculating by using an inverse trigonometric function, and storing the obtained value into Q [ K ] taking K as the index sequence number in the array Q; the inverse trigonometric function can be an arcsine function or an arccosine function;
the specific calculation formula of the arcsine function is adopted as follows;
Q[K]=arcsin(S[J]/A)
the specific calculation formula of the cosine function is adopted as follows;
Q[K]=arccos(S[J]/A)
wherein A is the signal amplitude calculated by measuring the amplitude of the noise suppression signal in the first big step; if a certain data S [ J ] in array S is encountered whose absolute value is greater than A, then that data is discarded.
B4, setting the value of R [ K ] in the array R with K as the index sequence number equal to J; then, accumulating the variable J, comparing whether the variable J is smaller than Z after accumulating the variable K, if so, executing the step B3, otherwise, executing the step C1;
fourthly, calculating the frequency of the signal to be measured; the method comprises the following specific steps:
c1, calculating the average value O of all elements in the array Q, and then calculating the average value B of all elements in the array R;
c2, defining three variables G, X and Y, and setting the initial values of the variables G, X and Y to be zero;
c3, obtaining data R [ G ] with G as an index sequence number in the array R, and subtracting the average value B to obtain a difference value W;
obtaining data Q [ G ] with G as an index sequence number in the array Q, and subtracting the average value O to obtain a difference value V;
multiplying the difference value W by the difference value V to obtain C;
increasing the value of the variable X by C;
c4, squaring the difference value W to obtain T;
increasing the value of the variable Y by T;
c5, after adding 1 to the variable G, if the value of G is less than Z, returning to execute the step C3, otherwise, calculating the instantaneous frequency f of the frequency modulation signal input from the data input 1 at the point P;
wherein F is the sampling signal frequency of the input data;
fifthly, calculating average frequency;
changing the point P to the outside of the triangular interval of the signals obtained in the step two pairs, and calculating the signal frequency of other intervals, namely repeating the step three and the step four until all data intervals are calculated once; so far, frequency values f can be obtained for many times, and the average value of the frequencies is calculated, namely the frequency of the input signal can be accurately measured; and the measured accurate frequency value is output from the output end.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (6)
1. The frequency modulation signal inverse triangle noise suppression and frequency measurement method is characterized in that: the method is realized by a frequency modulation signal inverse triangle noise suppression and frequency measurement demodulation system, wherein the frequency measurement demodulation system comprises a data input end, a memory, a processor and an output end;
the data input end inputs a signal to be tested and stores the signal in the memory;
the memory stores the signal to be tested obtained from the data input end; continuously storing N data logically in each measurement process to form a data structure of a one-dimensional array, which is expressed by Si;
the processor analyzes the data stored in the memory, calculates a triangular interval of the signal to be detected by measuring the amplitude of the noise suppression signal, performs inverse triangular transformation, calculates the frequency of the signal to be detected and calculates the average frequency of the signal to be detected, and obtains the instantaneous frequency f at the position with the index sequence number of i ═ P; the specific process is as follows:
firstly, measuring the amplitude of a noise suppression signal to obtain the instantaneous amplitude A of a signal to be detected after noise suppression is calculated; secondly, calculating the triangular interval of the signal to be measured, and storing the triangular interval in a variable D and a variable U, wherein the method comprises the following specific steps:
step a1, obtaining data S [ P ] with sequence number i-P position in the array S [ i ];
step A2, using variable K as cycle index sequence number, the initial value of K is equal to P;
step A3, comparing the size of S [ K ] and S [ K-1], if S [ K-1] is larger than S [ K ], executing step A4, otherwise, executing step A5;
step a4, K-1, execute step A3;
step A5, if the value of the variable K is less than P, the variable U is used for saving the value of K at the moment and then the step A6 is executed, otherwise the step A12 is executed;
step A6, setting the initial value of a variable K equal to P;
step A7, comparing the S [ K ] and S [ K +1], if S [ K +1] is less than S [ K ], executing step A8, otherwise, executing step A9 by a failed jump;
step A8, after adding 1 to the variable K, executing step A7;
step A9, if the value of the variable K is larger than P, the variable D is used for storing the value of K at the moment, then the step A10 is executed, otherwise, the step A12 is executed in failure;
step A10, respectively adopting the numerical value in the variable U, subtracting 1 from the numerical value in U, and adding 1 to the numerical value in U as an index number, obtaining data from the array S to obtain the S [ U ], S [ U-1], and S [ U +1], if the numerical value obtained by subtracting S [ U-1] from S [ U ] is larger than the numerical value obtained by subtracting S [ U +1] from S [ U ], adding 1 to the variable U;
step A11, respectively using the numerical value in the variable D, subtracting 1 from the numerical value in D, and adding 1 to the numerical value in D as an index number, obtaining data from the array S to obtain SD, SD-1, and SD +1, if the numerical value of subtracting SD +1 from SD is larger than the numerical value of subtracting S-1 from SD, subtracting 1 from the variable D; at this time, the variable U and the variable D store the triangular interval information of the signal to be detected, and the step B1 is executed;
the initial value of the step A12 and the step K is equal to P;
step A13, comparing the S [ K ] and the S [ K +1], if the S [ K +1] is larger than the S [ K ], executing step A14, otherwise, skipping to execute step A15;
step a14, K + K, execute step a 13;
step A15, adopting a variable U to store the K value at the moment;
the initial value of the step A16 and K is equal to P;
step A17, comparing S [ K ] with S [ K-1], if S [ K-1] is less than S [ K ], executing step A18, otherwise, executing step A19;
step a17 is executed after step a18, K ═ K-1;
step A19, storing the K value at the moment by adopting a variable D;
step A20, respectively adopting the numerical value in the variable U, subtracting 1 from the numerical value in U, and adding 1 to the numerical value in U as an index number, obtaining data from the array S to obtain S [ U ], S [ U-1], and S [ U +1], if the difference of subtracting S [ U-1] from S [ U ] is less than the difference of subtracting S [ U +1] from S [ U ], then changing U to U-1;
step A21, respectively using the numerical value in the variable D, the numerical value in D minus 1 and the numerical value in D plus 1 as index numbers, obtaining data from the array S, obtaining S [ D ], S [ D-1] and S [ D +1], if the difference between S [ D ] and S [ D +1] is smaller than the difference between S [ D ] and S [ D-1], then D is D-1; at this time, the triangle interval information of the signal to be detected is stored in the variable U and the variable D, and the step B1 is executed;
then, carrying out inverse triangle transformation on the signal to be detected, and the specific process is as follows:
b1, defining a one-dimensional array Q, wherein the number of elements in the array is represented by Z, and the calculation method of Z is as follows;
Z=|U-D|
defining a one-dimensional array R, wherein the number of elements in the array is also Z;
b2, defining a variable J to enable the value of J to be equal to U, then comparing the size of the variable U with that of the variable D, and enabling the variable J to be equal to the variable D if the variable U is larger than the variable D; and making the initial value of the variable K zero;
step B3, taking the variable J as the index sequence number of the array S, obtaining data S [ J ] from the array S, then calculating by using an inverse trigonometric function, and saving the obtained value in the Q [ K ] taking K as the index sequence number in the array Q;
step B4, setting the value of R [ K ] with K as index sequence number in the array R equal to J; then, accumulating the variable J, comparing whether the variable J is smaller than Z after accumulating the variable K, if so, executing the step B3, otherwise, executing the step C1;
and finally, calculating the frequency of the signal to be detected, and specifically comprising the following steps:
c1, calculating the average value O of all elements in the array Q, and then calculating the average value B of all elements in the array R;
step C2, defining three variables G, X and Y, and setting the initial values to be zero;
step C3, obtaining data R [ G ] with G as an index sequence number in the array R, and subtracting the average value B to obtain a difference value W;
obtaining data Q [ G ] with G as an index sequence number in the array Q, and subtracting the average value O to obtain a difference value V;
multiplying the difference value W and the difference value V to obtain a product C;
increasing the value of variable X by C, i.e., X ═ X + C;
step C4, after the difference value W is squared, a squared value T is obtained; changing Y to Y + T;
step C5, changing the variable G to G +1, if the value of G is less than Z, returning to execute the step C3, otherwise, calculating the instantaneous frequency f of the signal to be measured at the point P, which is input from the data input end;
and changing the point P to a position except the position obtained in the step A1, returning to the step A1 until all data intervals are calculated, calculating the average value of the instantaneous frequency f obtained from a plurality of data intervals, obtaining the average frequency of the signal to be measured, and outputting the average frequency from an output end.
2. A method of anti-triangular noise suppression and frequency measurement for a frequency modulated signal according to claim 1, characterized by: the original signal of the signal to be detected is a signal of superposed noise and contains a direct current signal, the original signal is a cosine signal of single frequency, and the instantaneous amplitude A is an unknown value; the frequency f is lower than the highest frequency upper limit value H; the amplitude of the original signal is greater than the amplitude of the noise signal;
requiring sampling an input signal to be tested at a fixed frequency F to obtain digital quantity data; ensuring that the sampling frequency F is more than 8 times of the highest frequency upper limit value H; the amplitude and frequency of the signal to be measured are kept constant during a single measurement.
3. A method of anti-triangular noise suppression and frequency measurement for a frequency modulated signal according to claim 1, characterized by: continuously storing N data logically in each measurement process to form a data structure of a one-dimensional array, which is expressed by Si; wherein S is an array name, and i is a subscript index sequence number; the minimum value of the subscript index serial number i is zero, and the maximum value is N minus 1; defining the decreasing direction of the subscript index sequence numbers as the left direction, and the increasing direction of the subscript index sequence numbers as the right direction.
4. A method of anti-triangular noise suppression and frequency measurement for a frequency modulated signal according to claim 1, characterized by: the process of calculating the instantaneous amplitude A of the signal to be measured after noise suppression by measuring the amplitude of the noise suppression signal is as follows:
firstly, calculating a direct current voltage L in a signal to be measured;
subtracting the direct current voltage L from each element in the array Si;
calculating the whole array S [ i ] after the direct current L is removed by adopting the following formula to obtain a root mean square value M of the signal to be measured;
calculating an absolute average value E by using the following formula;
then substituting the square mean root value M and the absolute average value E of the signal to be measured into the following formula to obtain the instantaneous amplitude A of the signal to be measured after noise suppression is calculated;
5. a method for inverse triangular noise suppression and frequency measurement of a frequency-modulated signal according to claim 1, characterized in that: in the step B3, in the inverse trigonometric function calculation, an inverse sine function or an inverse cosine function is adopted to calculate an array Q [ K ];
the specific calculation formula of the arcsine function is as follows;
Q[K]=arcsin(S[J]/A)
the specific calculation formula of the inverse cosine function is as follows;
Q[K]=arccos(S[J]/A)。
6. a method of anti-triangular noise suppression and frequency measurement for a frequency modulated signal according to claim 1, characterized by: and if the signal to be detected input by the data input end is an analog signal, the signal to be detected is converted by the analog-to-digital converter and then is sent to the data input end.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210283593.1A CN114624512A (en) | 2022-03-22 | 2022-03-22 | Frequency modulation signal inverse triangle noise suppression and frequency measurement method |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210283593.1A CN114624512A (en) | 2022-03-22 | 2022-03-22 | Frequency modulation signal inverse triangle noise suppression and frequency measurement method |
Publications (1)
Publication Number | Publication Date |
---|---|
CN114624512A true CN114624512A (en) | 2022-06-14 |
Family
ID=81904459
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202210283593.1A Pending CN114624512A (en) | 2022-03-22 | 2022-03-22 | Frequency modulation signal inverse triangle noise suppression and frequency measurement method |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN114624512A (en) |
-
2022
- 2022-03-22 CN CN202210283593.1A patent/CN114624512A/en active Pending
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2018188228A1 (en) | High-precision frequency measuring system and method | |
US6598004B1 (en) | Jitter measurement apparatus and its method | |
JP2006313162A (en) | System and method for calibrating time interleaved timing of data converter | |
US5243537A (en) | Method and apparatus for rapid measurement of AC waveform parameters | |
CN108519511B (en) | Time domain measurement method for frequency characteristic parameters of linear frequency modulation signals | |
CN110768661B (en) | Phase-locked amplifier based on neural network | |
CN113791268A (en) | Method and device for measuring effective value of high-frequency alternating voltage and storage medium | |
US6820017B1 (en) | Method for determining the amplitude and phase angle of a measuring signal corresponding to a current or voltage of an electrical power supply network | |
CN105044459B (en) | A kind of harmonic analysis method | |
CN107579734B (en) | Signal processing method, signal processing device, storage medium and processor | |
EP0058050B1 (en) | Measuring method | |
CN114624512A (en) | Frequency modulation signal inverse triangle noise suppression and frequency measurement method | |
CN109716720A (en) | The splicing of time sequencing frequency spectrum | |
CN108037359B (en) | Power grid frequency measuring circuit for eliminating flicker and inter-harmonic interference | |
CN109521269A (en) | A kind of am signals digitlization frequency measuring method | |
CN113805042B (en) | Time delay measuring device and testing method | |
US20220187351A1 (en) | Waveform measuring method | |
de Oliveira et al. | Instantaneous frequency measurement subsystem implementation using low-cost microcontroller | |
CN109633251A (en) | A kind of I/F circuit integral voltage peak-to-peak value method for solving and device | |
CN114629761B (en) | Frequency modulation signal inverse triangular frequency measurement demodulation method | |
CN114720773A (en) | Resistance measuring device and terminal equipment | |
US4181949A (en) | Method of and apparatus for phase-sensitive detection | |
US9759751B1 (en) | Line cycle correlated spectral analysis for power measurement systems | |
EP3569986B1 (en) | Position sensing device | |
JPH04105073A (en) | Measuring device for effective value |
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 |