Pulse position modulation signal noise reduction method, device and equipment based on signal suppression

Abstract

The present invention provides a method, device and equipment for reducing noise of a pulse position modulation signal based on signal suppression. The noise reduction method comprises: S1, bandpass filtering the received electromagnetic logging signal to remove out-of-band interference and noise, and obtain a signal to be processed x(n); S2, constructing a signal suppression reference signal xr(n) according to the characteristics of the wireless electromagnetic logging signal; S3, using the wireless electromagnetic logging signal and the reference signal as input, using a recursive least squares adaptive filter to suppress the signal, and outputting a filter-synthesized cancellation signal xj(n); S4, low-pass filtering the cancellation signal xj(n) to obtain a useful signal s'(n) after noise reduction. The present invention improves the signal-to-noise ratio of the processed signal on the basis of traditional filtering technology, thereby improving the reliability and practicability of the logging signal transmission. The method is novel, has a small amount of calculation, and has strong universality. It has a good development prospect in the field of electromagnetic signal detection such as oil logging.

Description

Technical Field

[0001] The present invention relates to the technical field of measurement while drilling data signal processing, and in particular to a pulse position modulation signal denoising method based on signal suppression, a pulse position modulation signal denoising device based on signal suppression, a computer device for implementing the denoising method, and a computer-readable storage medium storing a computer program. Background Art

[0002] Wireless electromagnetic logging signals are an important means of data transmission for electromagnetic wave wireless measurement while drilling, so the reliability of wireless electromagnetic logging signals directly affects the effective transmission of logging data. In order to save energy of downhole transmitters and increase working time, wireless electromagnetic logging signals mostly use pulse position modulation.

[0003] The purpose of noise suppression is to improve the signal-to-noise ratio of the signal and improve the reliability of data transmission. The current electromagnetic logging signal noise suppression mostly improves the signal-to-noise ratio through filtering. When the signal-to-noise ratio is very low, or the noise band overlaps the signal band, the filtering method will cause great damage to the original signal, thus affecting the noise reduction effect.

[0004] For example, the Chinese patent document entitled A Wireless Remote Receiving Device for Electromagnetic Wave Measurement While Drilling System and Its Measurement Method and Application and Publication No. CN103061754A published on April 24, 2013 records a wireless remote receiving device, which includes a receiving antenna array and a remote receiving unit; the remote receiving unit includes a central processing unit, a control circuit, a wireless transceiver module and a power supply; the wireless transceiver module is connected to the central processing unit through the control circuit. A device for remotely receiving electromagnetic wave measurement while drilling signals is developed, which is used for remotely receiving measurement signals in electromagnetic measurement while drilling systems. DSP technology and array signal processing technology are used to suppress well site noise, and remote reception of weak electromagnetic signals is achieved by reasonably arranging array elements and combining with advanced digital signal processing algorithms, which effectively improves the adaptability of the electromagnetic wave measurement while drilling system to different formations, improves processing gain and receiving sensitivity, and increases measurement depth.

[0005] The Chinese patent document entitled "A Ground Signal Processing Device for Measurement While Drilling" and published on May 3, 2017 and with the publication number CN106609669A describes a signal processing device, which includes: a first preamplifier module for amplifying received electromagnetic wave signals; a second preamplifier module for amplifying received mud pulse signals; a signal conditioning module for conditioning and outputting the signals output by the first preamplifier module and the second preamplifier module; and a central processing module for decoding and outputting the signals output by the signal conditioning module. The device is characterized in that it can receive and process and decode two signals, electromagnetic wave signals and mud pulse pressure signals.

[0006] The above patent documents have their advantages, but also have many disadvantages and limitations. The traditional noise reduction method is a passive noise reduction method, which reduces noise by noise and does not make full use of the characteristics of the signal itself. Therefore, it is necessary to form a noise reduction method based on signal suppression to improve the signal-to-noise ratio and restore the original characteristics of the required signal to the greatest extent. Summary of the invention

[0007] The purpose of the present invention is to solve at least one of the above-mentioned deficiencies in the prior art. For example, one of the purposes of the present invention is to provide a method for reducing noise of a pulse position modulation signal based on signal suppression, thereby solving the technical problem that the existing signal processing technology cannot distinguish the desired signal in the time domain and frequency domain when the signal-to-noise ratio is low and the noise interference is in the same frequency band as the signal.

[0008] In order to achieve the above-mentioned purpose, the present invention provides a pulse position modulation signal denoising method based on signal suppression, the denoising method comprising the following steps: S1, bandpass filtering the received electromagnetic logging signal to remove out-of-band interference and noise, and obtain the signal to be processed x(n); S2, constructing a signal suppression reference signal xr(n) according to the characteristics of the wireless electromagnetic logging signal; S3, taking the wireless electromagnetic logging signal and the reference signal as input, using a recursive least squares adaptive filter to suppress the signal, and outputting a cancellation signal xj(n) synthesized by the filter; S4, low-pass filtering the cancellation signal xj(n) to obtain the useful signal s'(n) after denoising.

[0009] In an exemplary embodiment of the pulse position modulation signal noise reduction method based on signal suppression of the present invention, step S2 may specifically include the following sub-steps: S21, based on the characteristics of the wireless electromagnetic logging signal, setting the frequency f0 of the reference signal and the sampling frequency f s ; S22, based on the frequency f0 and the sampling frequency f s , construct the signal suppression reference signal xr(n) = sin(2×pi×f0×m / f s ), where m is the reference signal sample point sequence number, m = 0, 1, …, N.

[0010] In an exemplary embodiment of the pulse position modulation signal denoising method based on signal suppression of the present invention, step S3 may specifically include the following sub-steps: S31, setting recursive least squares adaptive filter parameters and parameter initialization; S32, using the reference signal xr(n) and the recursive least squares adaptive filter to synthesize the cancellation signal xj(n); S33, based on the reference signal xr(n) and the cancellation signal xj(n), determining the error signal e(n); S34, using the error signal e(n), using the RLS criterion to update the recursive least squares adaptive filter coefficients; S35, repeating sub-steps S32 to S34 until the processing of x(n) is completed.

[0011] In an exemplary embodiment of the pulse position modulation signal denoising method based on signal suppression of the present invention, in sub-step S31, the recursive least squares adaptive filter parameters may include a filter length p and a forgetting factor λ.

[0012] In an exemplary embodiment of the pulse position modulation signal denoising method based on signal suppression of the present invention, the parameter initialization may include: initializing the filter weight coefficient according to Formula 1, initializing the input signal sliding window according to Formula 2,

[0013]

[0014] h[n]=[xr[n]xr[n-1]......xr[n-p+1]] T (2)

[0015] In formula (1) and formula (2), is the filter weight coefficient; h[n] is the input signal sliding window; p is the filter length; n is the unit time; is the filter tap coefficient.

[0016] In an exemplary embodiment of the pulse position modulation signal denoising method based on signal suppression of the present invention, the calculation formula of the cancellation signal xj(n) may be:

[0017]

[0018] In formula (3), xj[n] is a data in the cancellation signal xj(n) sequence, h[n] is the input signal sliding window, is the filter weight coefficient.

[0019] In an exemplary embodiment of the pulse position modulation signal noise reduction method based on signal suppression of the present invention, the calculation formula of the error signal e(n) can be:

[0020]

[0021] In formula (4), e(n) is the error signal, x[n] is a data in the sequence of the signal to be processed x(n), h[n] is the input signal sliding window, is the filter weight coefficient.

[0022] In an exemplary embodiment of the pulse position modulation signal denoising method based on signal suppression of the present invention, in sub-step S34, the filter weight coefficient can be updated according to equations (5) to (7):

[0023]

[0024]

[0025] Φ[n]=(IK[n]h T [n])Φ[n-1] (7)

[0026] In formula (5) to formula (7), is the filter weight coefficient, K[n] is the intermediate variable matrix, e[n] is the error signal, h[n] is the input signal sliding window, λ is the forgetting factor, I is the unit matrix, and Φ[n] is the intermediate variable matrix.

[0027] On the other hand, the present invention provides a pulse position modulation signal noise reduction device based on signal suppression, the noise reduction device includes a first signal processing unit, a construction unit, a second signal processing unit and a third signal processing unit, wherein the first signal processing unit is configured to perform bandpass filtering on the received electromagnetic logging signal to remove out-of-band interference and noise to obtain a signal to be processed x(n); the construction unit is configured to construct a signal suppression reference signal xr(n) according to the characteristics of the wireless electromagnetic logging signal; the second signal processing unit is connected to the first signal processing unit and the construction unit respectively, and is configured to take the wireless electromagnetic logging signal and the reference signal as input, use a recursive least squares adaptive filter to perform signal suppression, and output a filter-synthesized cancellation signal xj(n); the third signal processing unit is connected to the second signal processing unit, and is configured to perform low-pass filtering on the cancellation signal xj(n) to obtain a useful signal s'(n) after noise reduction.

[0028] In another aspect, the present invention provides a computer device, comprising: a processor; and a memory storing a computer program, wherein when the computer program is executed by the processor, the pulse position modulation signal noise reduction method as described above is implemented.

[0029] According to another aspect of the present invention, there is provided a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the pulse position modulation signal noise reduction method as described above is implemented.

[0030] Compared with the prior art, the beneficial effects of the present invention include at least one of the following:

[0031] (1) The present invention can solve the technical problem that the learned signal cannot be distinguished in the time domain and frequency domain due to the low signal-to-noise ratio and the noise interference in the same frequency band as the signal;

[0032] (2) The present invention can effectively suppress noise and improve the signal-to-noise ratio of the signal under low signal-to-noise ratio conditions;

[0033] (3) The present invention restores the original characteristics of the required signal to the greatest extent possible, thereby improving the reliability of electromagnetic logging signal transmission;

[0034] (4) The present invention improves the signal-to-noise ratio of the processed signal on the basis of traditional filtering technology, thereby improving the reliability and practicality of logging signal transmission. The method is novel, has small calculation amount, strong universality, and has good development prospects in the field of electromagnetic signal detection such as oil logging. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The above and other objects and / or features of the present invention will become more apparent through the following description in conjunction with the accompanying drawings, in which:

[0036] Figure 1 A schematic flow chart of a noise reduction method is shown of an exemplary embodiment of a pulse position modulation signal noise reduction method based on signal suppression of the present invention.

[0037] Figure 2 A schematic diagram of a signal suppression denoising technology model is shown of an exemplary embodiment of a pulse position modulation signal denoising method based on signal suppression of the present invention.

[0038] Figure 3A A schematic diagram of an original signal of an electromagnetic logging signal is shown, which is an exemplary embodiment of a pulse position modulation signal noise reduction method based on signal suppression of the present invention; Figure 3B A schematic diagram of a superimposed noise signal is shown of an exemplary embodiment of a pulse position modulation signal noise reduction method based on signal suppression of the present invention; Figure 3C A schematic diagram of a denoised output signal of an exemplary embodiment of a pulse position modulation signal denoising method based on signal suppression of the present invention is shown.

[0039] Figure 4 A schematic structural diagram of a noise reduction device is shown which is an exemplary embodiment of a pulse position modulation signal noise reduction device based on signal suppression of the present invention.

[0040] Figure 5A schematic diagram of the computer device structure of an exemplary embodiment of the pulse position modulation signal noise reduction device based on signal suppression of the present invention is shown.

[0041] Description of reference numerals:

[0042] 100 - signal noise reduction device, 101 - first signal processing unit, 102 - construction unit, 103 - second signal processing unit, 104 - third signal processing unit, 200 - computer equipment, 201 - memory, 201 - processor. DETAILED DESCRIPTION

[0043] Hereinafter, the pulse position modulation signal noise reduction method, device and apparatus based on signal suppression of the present invention will be described in detail in conjunction with exemplary embodiments.

[0044] It should be noted that “first”, “second”, “third”, etc. are merely for the convenience of description and distinction and cannot be understood as indicating or implying relative importance.

[0045] In order to solve the defects of traditional electromagnetic logging signal noise suppression technology and improve the reliability and practicality of logging signal transmission, the present invention proposes a pulse position modulation signal noise reduction method based on signal suppression. This method suppresses the useful components, separates the useless information (noise), and then restores the useful information in the received signal to suppress the noise. First, the electrical logging signal is bandpass filtered, and then a signal suppression reference signal is constructed. Then, recursive least squares (RLS) adaptive filtering is used to suppress the signal, and finally low-pass filtering is performed to obtain the useful signal after noise reduction.

[0046] Specifically, the present invention provides a pulse position modulation signal noise reduction method based on signal suppression.

[0047] In an exemplary embodiment of the present invention, a pulse position modulation signal noise reduction method based on signal suppression specifically includes the following steps:

[0048] S1. Perform bandpass filtering on the received electromagnetic logging signal to remove out-of-band interference and noise, and obtain a signal to be processed x(n).

[0049] S2. Construct a signal suppression reference signal xr(n) according to the characteristics of the wireless electromagnetic logging signal.

[0050] S3. Using the wireless electromagnetic logging signal and the reference signal as input, a recursive least square adaptive filter is used to suppress the signal, and a cancellation signal xj(n) synthesized by the filter is output.

[0051] S4. Perform low-pass filtering on the cancellation signal xj(n) to obtain a useful signal s′(n) after noise reduction.

[0052] In this embodiment, step S2 may specifically include the following sub-steps:

[0053] S21, based on the characteristics of the wireless electromagnetic logging signal, set the reference signal frequency f0 and the sampling frequency f s .

[0054] S22, based on frequency f0 and sampling frequency f s , construct the signal suppression reference signal xr(n) = sin(2×pi×f0×m / f s ), where m is the reference signal sample point sequence number, m=0, 1, ..., N.

[0055] In this embodiment, step S3 may specifically include the following sub-steps:

[0056] S31, setting recursive least squares adaptive filter parameters and parameter initialization.

[0057] The recursive least squares adaptive filter parameters may include a filter length p and a forgetting factor λ.

[0058] The filter weight coefficient can be initialized according to Formula 1, and the input signal sliding window can be initialized according to Formula 2.

[0059]

[0060] h[n]=[xr[n]xr[n-1]......xr[-p+1]] T (2)

[0061] In formula (1) and formula (2), is the filter weight coefficient; h[n] is the input signal sliding window; p is the filter length; n is the unit time; is the filter tap coefficient.

[0062] S32. Use the reference signal xr(n) and a recursive least squares adaptive filter to synthesize a cancellation signal xj(n).

[0063] For example, the calculation formula of the cancellation signal xj(n) can be:

[0064]

[0065] In formula (3), xj[n] is a data in the cancellation signal xj(n) sequence, h[n] is the input signal sliding window, is the filter weight coefficient.

[0066] S33. Determine an error signal e(n) based on the reference signal xr(n) and the cancellation signal xj(n).

[0067] For example, the error signal e(n) may be calculated as:

[0068]

[0069] In formula (4), e(n) is the error signal, x[n] is a data in the sequence of the signal to be processed x(n), h[n] is the input signal sliding window, is the filter weight coefficient.

[0070] S34, using the error signal e(n) and adopting the RLS criterion to update the recursive least squares adaptive filter coefficients.

[0071] For example, the filter weight coefficients may be updated according to equations (5) to (7).

[0072]

[0073]

[0074] Φ[n]=(IK[n]h T [n])Φ[n-1] (7)

[0075] In formula (5) to formula (7), is the filter weight coefficient, K[n] is the intermediate variable matrix, e[n] is a data in the error signal e(n) sequence, h[n] is the input signal sliding window, λ is the forgetting factor, I is the unit matrix, and Φ[n] is the intermediate variable matrix.

[0076] S35. Repeat sub-steps S32 to S34 until the processing of x(n) is completed.

[0077] The pulse position modulation signal denoising method based on signal suppression of the present invention makes full use of the characteristics of the signal, is applicable to all types of common noise and narrowband interference, and can be used as a processing method for improving the signal-to-noise ratio of other signals (such as pulse amplitude modulation signals, FSK signals, etc.).

[0078] Another aspect of the present invention provides a pulse position modulation signal noise reduction device based on signal suppression.

[0079] In another exemplary embodiment of the present invention, a pulse position modulation signal noise reduction device based on signal suppression includes a first signal processing unit, a construction unit, a second signal processing unit, and a third signal processing unit.

[0080] The first signal processing unit is configured to perform bandpass filtering on the received electromagnetic logging signal to remove out-of-band interference and noise, and obtain a signal to be processed x(n).

[0081] The construction unit is configured to construct a signal suppression reference signal xr(n) according to the wireless electromagnetic logging signal characteristics.

[0082] The second signal processing unit is connected to the first signal processing unit and the construction unit respectively, and is configured to take the wireless electromagnetic logging signal and the reference signal as input, use a recursive least squares adaptive filter to suppress the signal, and output a filter-synthesized cancellation signal xj(n).

[0083] The third signal processing unit is connected to the second signal processing unit, and is configured to perform low-pass filtering on the cancellation signal xj(n) to obtain a useful signal s′(n) after noise reduction.

[0084] The pulse position modulation signal noise reduction method according to the present invention can be programmed as a computer program and the corresponding program code or instructions can be stored in a computer-readable storage medium. When the program code or instructions are executed by a processor, the processor executes at least one of the above-mentioned pulse position modulation signal noise reduction methods. The above-mentioned processor and memory can be included in a computer device.

[0085] According to an exemplary embodiment of another aspect of the present invention, a computer-readable storage medium storing a computer program is also provided. The computer-readable storage medium stores a computer program that, when executed by a processor, causes the processor to perform a pulse position modulation signal noise reduction method according to the present invention. The computer-readable recording medium is any data storage device that can store data read out by a computer system. Examples of computer-readable recording media include: read-only memory, random access memory, read-only optical disk, magnetic tape, floppy disk, optical data storage device, and carrier wave (such as data transmission through the Internet via a wired or wireless transmission path).

[0086] According to another exemplary embodiment of the present invention, a computer device is provided. The computer device includes a processor and a memory. The memory is used to store a computer program. The computer program is executed by the processor so that the processor executes the computer program of the pulse position modulation signal noise reduction method according to the present invention.

[0087] In order to better understand the above exemplary embodiments of the present invention, they are further described below with reference to the accompanying drawings and specific examples.

[0088] Example 1

[0089] like Figure 1 As shown, the pulse position modulation signal noise reduction method based on signal suppression in this example includes the following steps.

[0090] Step 1: According to the characteristics of wireless electromagnetic logging signals, a bandpass filter is designed to perform bandpass filtering on the received electromagnetic logging signals to remove out-of-band interference and noise, and eliminate baseline drift to obtain the signal to be processed x(n).

[0091] In actual use, the noise reduction method of signal suppression can directly process the received electromagnetic logging signal. In order to objectively evaluate the performance of the present invention, this example uses matlab software to construct the electromagnetic logging signal according to the characteristics of the electromagnetic logging signal, and uses a bandpass filter to filter to obtain the signal x(n) to be processed.

[0092] Step 2: According to the characteristics of wireless electromagnetic logging signals, construct a signal suppression reference signal xr(n).

[0093] xr(n)=A×sin(2×pi×f0×m / f s ), where A = 1, m is the reference signal sample point sequence number, m = 0, 1, ..., N, f0 is the frequency of the pulse position modulation signal pulse, f s is the sampling frequency.

[0094] Step 3: Taking the received wireless electromagnetic logging signal and the reference signal as input, a recursive least square (RLS) adaptive filter is used to suppress the signal and output the cancellation signal xj(n) synthesized by the filter.

[0095] Specifically, the RLS adaptive filter is used to process x(n) and xr(n) as follows:

[0096] a) Set the filter length p and forgetting factor λ, and initialize the filter weight coefficients according to equations 1 and 2 And the input signal sliding window h[n].

[0097]

[0098] h[n]=[xr[n]xr[n-1]……xr[n-p+1]] T (2)

[0099] In formula (1) and formula (2), is the filter weight coefficient; h[n] is the input signal sliding window; p is the filter length; n is the unit time; is the tap coefficient of the filter.

[0100] b) Calculate the synthetic cancellation signal xj[n] according to equation 3.

[0101]

[0102] In formula (3), xj[n] is the cancellation signal, h[n] is the input signal sliding window, is the filter weight coefficient.

[0103] c) Calculate the error signal e(n) according to equation 4.

[0104]

[0105] In formula (4), e(n) is the error signal, x[n] is a data in the sequence of the signal to be processed x(n), h[n] is the input signal sliding window, is the filter weight coefficient.

[0106] d) Update the filter weight coefficient according to equation 5, equation 6 and equation 7

[0107]

[0108]

[0109] Φ[n]=(IK[n]h T [n])Φ[n-1] (7)

[0110] In formula (5) to formula (7), is the filter weight coefficient, K[n] is the intermediate variable matrix, e[n] is the error signal, h[n] is the input signal sliding window, λ is the forgetting factor, I is the unit matrix, and Ф[n] is the intermediate variable matrix.

[0111] e) Repeat the calculation of the synthetic cancellation signal, the calculation of the error signal and the iterative update of the filter coefficients until the signal processing is completed.

[0112] Step 4: Perform low-pass filtering on xj(n) to obtain the noise-reduced signal s'(n).

[0113] In order to highlight the superiority of the method of the present invention, this embodiment constructs an electromagnetic logging signal with superimposed noise according to the characteristics of the electromagnetic logging signal to conduct a simulation experiment (the signal-to-noise ratio in the simulation experiment is 3dB), and the process and results are described as follows.

[0114] The original electromagnetic logging signal consists of a synchronization header and a data segment, and its mathematical description is as follows:

[0115] Signal unit: ceil = sin(2πf0m / f s ), n=0,1,..,39, f0=5Hz, f s =200Hz.

[0116] Synchronization header: [ceil ceil ceil], consisting of 3 consecutive signal units.

[0117] Data segment: ∑ i a i *ceil,a i The binary data to be sent.

[0118] According to the signal characteristics, the test original signal s(n) was constructed using matlab software.

[0119] According to the set signal-to-noise ratio, the noise n(t) is generated directly by the Gaussian noise generation function awgn of the MATLAB software.

[0120] The noise and the original signal are superimposed to simulate the received wireless electromagnetic logging signal, x(n)=s(n)+n(t).

[0121] The signal suppression and noise reduction technology of the present invention is used to process x(n), the signal-to-noise ratio is set to 5dB, and the noise-reduced signal s'(n) is output.

[0122] In order to qualitatively analyze the effectiveness of this technology, we qualitatively analyzed the advantages of signal suppression noise reduction technology through the signal-to-noise ratio. The results show that signal suppression noise reduction technology can successfully separate noise and signal under low signal-to-noise ratio conditions.

[0123] Figure 2 Schematic diagram of the model representing the signal suppression and denoising method. The basic principle is to use the received wireless electromagnetic logging signal x(n) and the reference signal xr(n) as input, use a recursive least squares (RLS) adaptive filter to suppress the signal, and output the cancellation signal xj(n) synthesized by the filter. Figure 3A represents the original signal s(n), Figure 3B represents the signal x(n) with superimposed noise, and Figure 3C represents the denoised signal s'(n), where Figure 3A , Figure 3B and Figure 3C The horizontal axis is the sample point, and the vertical axis is the amplitude, without unit.

[0124] It is not difficult to see that the method of the present invention can effectively suppress noise and improve the signal-to-noise ratio of the signal under low signal-to-noise ratio conditions. This technology proposes new ideas and methods for noise suppression from different perspectives, which has a strong guiding significance for noise suppression.

[0125] This example proposes a pulse position modulation signal noise reduction method based on signal suppression. Compared with the traditional noise reduction method, there is an essential difference between the two. The noise reduction method based on signal suppression proposed in this example makes full use of the characteristics of pulse position modulation of wireless electromagnetic logging signals. It is an active noise reduction method that can effectively improve the signal-to-noise ratio, restore the original characteristics of the required signal to the greatest extent, and improve the reliability of electromagnetic logging signal transmission. The noise reduction technology based on signal suppression proposes a new idea and new method for noise suppression from a different perspective, which has great guiding significance for noise suppression.

[0126] Example 2

[0127] like Figure 4 As shown, the signal noise reduction device 100 includes a first signal processing unit 101 , a construction unit 102 , a second signal processing unit 103 and a third signal processing unit 104 .

[0128] The first signal processing unit 101 is configured to perform bandpass filtering on the received electromagnetic logging signal to remove out-of-band interference and noise, and obtain a signal to be processed x(n).

[0129] The construction unit 102 is configured to construct a signal suppression reference signal xr(n) according to the characteristics of the wireless electromagnetic logging signal.

[0130] The second signal processing unit 103 is connected to the first signal processing unit 101 and the construction unit 102 respectively, and is configured to take the wireless electromagnetic logging signal and the reference signal as input, use a recursive least squares adaptive filter to perform signal suppression, and output a filter-synthesized cancellation signal xj(n).

[0131] The third signal processing unit 104 is connected to the second signal processing unit 103 and is configured to perform low-pass filtering on the cancellation signal xj(n) to obtain a useful signal s′(n) after noise reduction.

[0132] Example 3

[0133] like Figure 5 As shown, a computer device 200 includes a memory 201 and a processor 202. The memory 201 is used to store a computer program. The computer program is executed by the processor so that the processor executes the computer program of the pulse position modulation signal noise reduction method according to the present invention.

[0134] In summary, the beneficial effects of the present invention include at least one of the following:

[0135] (1) The present invention can solve the technical problem that the learned signal cannot be distinguished in the time domain and frequency domain due to the low signal-to-noise ratio and the noise interference in the same frequency band as the signal;

[0136] (2) The present invention can effectively suppress noise and improve the signal-to-noise ratio of the signal under low signal-to-noise ratio conditions;

[0137] (3) The present invention restores the original characteristics of the required signal to the greatest extent possible, thereby improving the reliability of electromagnetic logging signal transmission;

[0138] (4) The present invention improves the signal-to-noise ratio of the processed signal on the basis of traditional filtering technology, thereby improving the reliability and practicality of logging signal transmission. The method is novel, has small calculation amount, strong universality, and has good development prospects in the field of electromagnetic signal detection such as oil logging.

[0139] Although the present invention has been described above in conjunction with the exemplary embodiments and the accompanying drawings, it should be apparent to those skilled in the art that various modifications may be made to the above-described embodiments without departing from the spirit and scope of the claims.

Claims

1. A pulse position modulation signal denoising method based on signal suppression, characterized in that: The noise reduction method comprises the following steps: S1. Bandpass filter the received electromagnetic logging signal to remove out-of-band interference and noise to obtain the signal to be processed x(n); S2. Constructing a signal suppression reference signal xr(n) according to the characteristics of the wireless electromagnetic logging signal; S3, taking the signal to be processed and the signal suppression reference signal as input, performing signal suppression using a recursive least squares adaptive filter, and outputting a cancellation signal xj(n) synthesized by the filter; S4, performing low-pass filtering on the cancellation signal xj(n) to obtain a useful signal s'(n) after noise reduction; Step S3 specifically includes the following sub-steps: S31, setting recursive least squares adaptive filter parameters and parameter initialization; S32, synthesizing a cancellation signal xj(n) using the signal suppression reference signal xr(n) and a recursive least squares adaptive filter; S33, determining an error signal e(n) based on the signal to be processed x(n) and the cancellation signal xj(n); S34, using the error signal e(n) and the RLS criterion to update the recursive least squares adaptive filter coefficients; S35, repeat sub-steps S32 to S34 until the processing of x(n) is completed; The parameter initialization includes: initializing the filter weight coefficient according to Formula 1, initializing the input signal sliding window according to Formula 2, h[n]=[xr[n]xr[n-1]......xr[n-p+1]] T (2) In formula (1) and formula (2), is the filter weight coefficient; h[n] is the input signal sliding window; p is the filter length; n is the unit time; is the filter tap coefficient.

2. The pulse position modulation signal denoising method based on signal suppression according to claim 1, characterized in that: Step S2 specifically includes the following sub-steps: S21, based on the characteristics of the wireless electromagnetic logging signal, setting the frequency f0 and sampling frequency f of the signal suppression reference signal s ; S22, based on the frequency f0 and the sampling frequency f s , construct the signal suppression reference signal xr(n)=sin(2×pi×f0×m / f s ), where m is the sample point sequence number of the signal suppression reference signal, m=0,1,…,N.

3. The pulse position modulation signal denoising method based on signal suppression according to claim 1, characterized in that: In sub-step S31, the recursive least squares adaptive filter parameters include filter length p and forgetting factor λ.

4. The pulse position modulation signal denoising method based on signal suppression according to claim 1, characterized in that: The calculation formula of the cancellation signal xj(n) is: In formula (3), xj[n] is a data in the cancellation signal xj(n) sequence, h[n] is the input signal sliding window, is the filter weight coefficient.

5. The pulse position modulation signal noise reduction method based on signal suppression according to claim 4, characterized in that: The calculation formula of the error signal e(n) is: In formula (4), e(n) is the error signal, x[n] is a data in the sequence of the signal to be processed x(n), h[n] is the input signal sliding window, is the filter weight coefficient.

6. The pulse position modulation signal noise reduction method based on signal suppression according to claim 5, characterized in that: In sub-step S34, the filter weight coefficient is updated according to equations (5) to (7), Φ[n]=(IK[n]h T [n])Φ[n-1] (7) In formula (5) to formula (7), is the filter weight coefficient, K[n] is the intermediate variable matrix, e[n] is the error signal, h[n] is the input signal sliding window, λ is the forgetting factor, I is the unit matrix, and Ф[n] is the intermediate variable matrix.

7. A pulse position modulation signal noise reduction device based on signal suppression, characterized in that: The noise reduction device is used to implement the noise reduction method according to any one of claims 1 to 6, and comprises a first signal processing unit, a construction unit, a second signal processing unit and a third signal processing unit, wherein: The first signal processing unit is configured to perform bandpass filtering on the received electromagnetic logging signal to remove out-of-band interference and noise, and obtain a signal to be processed x(n); The construction unit is configured to construct a signal suppression reference signal xr(n) according to the characteristics of the wireless electromagnetic logging signal; The second signal processing unit is connected to the first signal processing unit and the construction unit respectively, and is configured to take the signal to be processed and the signal suppression reference signal as input, perform signal suppression using a recursive least squares adaptive filter, and output a cancellation signal xj(n) synthesized by the filter; The third signal processing unit is connected to the second signal processing unit, and is configured to perform low-pass filtering on the cancellation signal xj(n) to obtain a useful signal s'(n) after noise reduction.

8. A computer device, characterized in that: The computer device comprises: Processor; and A memory stores a computer program, and when the computer program is executed by a processor, the pulse position modulation signal noise reduction method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the pulse position modulation signal noise reduction method as claimed in any one of claims 1 to 6 is implemented.

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