An ultra-low frequency atmospheric noise cancellation system, method and apparatus

Abstract

The application provides an ultra-low frequency atmospheric noise elimination system, method and device, the system comprises: a data preprocessing module, a first data processing module and a second data processing module, the data preprocessing module preprocesses a time domain signal, the first data processing module filters and processes an ultra-low frequency primary noise elimination time domain signal to obtain an ultra-low frequency secondary noise elimination time domain signal; the second data processing module converts the ultra-low frequency secondary noise elimination time domain signal into a frequency domain signal, processes the frequency domain signal, and then converts the frequency domain signal into a time domain signal to obtain an ultra-low frequency atmospheric noise elimination signal. The method and device are based on the above system. The application firstly converts a part of noise power in the time domain signal into signal power, then filters and processes the time domain signal, and then converts the time domain signal into a frequency domain signal to eliminate noise and then converts the frequency domain signal into a time domain signal, so that decoding is facilitated, and the power of effective information is relatively increased.

Description

Technical Field

[0001] This invention relates to the field of noise cancellation, and more particularly to an ultra-low frequency atmospheric noise cancellation system, method, and apparatus. Background Technology

[0002] The content in this section provides only background information related to this disclosure and may not constitute prior art.

[0003] Ultra-low frequency (ULF) systems are wireless communication systems that typically operate in the range of tens to hundreds of hertz. Due to their long transmission distances, strong anti-interference capabilities, and excellent penetration, ULF systems play a crucial role in many applications. They are commonly used to monitor earthquakes and crustal movements, measure tides and waves in the ocean, record changes in the Earth's rotation and magnetic field, and for the detection and control of power transmission and distribution networks. Furthermore, ULF systems also play a key role in space science research and magnetic resonance imaging (MRI).

[0004] While research on ultra-low frequency (ULF) communication has yielded some results both domestically and internationally, the unique characteristics of its operating frequency band, coupled with extremely high impulse noise (UMP) leading to low spectral efficiency and reduced anti-interference capabilities, make research into comprehensive solutions for eliminating atmospheric impulse noise in ULF systems and improving system information transmission crucial and meaningful.

[0005] The first step is to construct an atmospheric impulse noise model. For a long time, atmospheric noise has been extensively studied, but due to its complex characteristics and diverse distribution patterns, unified research has become difficult. Researchers analyze monitoring data and statistically study the variation of atmospheric noise with time and location to establish noise models. Studying the statistical characteristics of atmospheric noise amplitude is the foundation for constructing a noise model. First, the amplitude probability characteristic curve is statistically analyzed based on the collected noise data. Then, the noise model parameters are estimated to achieve a best fit to the actual curve. It is worth noting that two classic impulse noise models have emerged in the past few decades, significantly impacting atmospheric noise research. In the 1970s, D. Middleton proposed the Class model and its parameter estimation method, a study that continues to evolve. In 1994, C.L. Nikia and his student Min Shao expanded the application of stable distribution noise in impulse detection. Douglas analyzed the maximum likelihood ratio receiver performance under stable distribution atmospheric noise and methods for estimating stable distribution parameters. With the progress of research, in recent years, scholars have proposed two-parameter Gauss-Cauchy models and their various variants, which are gradually becoming more common.

[0006] Research on atmospheric noise suppression methods has gradually emerged based on noise models. Wang Pingbo et al. proposed two impulse noise suppression methods: one based on local optimal detection processing of the probability density function and its derivative, and the other based on Gaussianization processing of noise. They analyzed the impact of these two methods on changes in data samples. However, Chen Zhiyi et al. subsequently pointed out that although the stable distribution can well describe the long-tail characteristics of impulse noise such as atmospheric noise, its density function usually does not have a closed-form expression, thus requiring a large amount of numerical calculation and making its application cumbersome. To solve this problem, researchers have improved the structure of the stable distribution model, for example, by using other nonlinear transformation functions to replace the original transformation function, and combining it with matched filtering processing, such as classic methods like clippers and nullifiers. Zhang Zhipeng et al. proposed using wavelet denoising to eliminate the influence of random noise in the data, using median filtering to suppress impulse interference that cannot be filtered out by wavelet filtering, and using combined filtering design to preprocess the data to improve the noise suppression effect. In addition, Fu Zhen et al. proposed using MSK modulation to effectively suppress atmospheric interference in ultra-low frequency systems. However, these traditional methods have many shortcomings. For typical limiters, the remaining noise energy after filtering can significantly interfere with the signal. Furthermore, this method of filtering infinitely broadens the noise in the time domain, making its impact on the useful signal even more severe. Clippers primarily damage the signal waveform during processing, hindering demodulation and ultimately bit error rate control. Moreover, the clipping level increases with atmospheric noise intensity, further degrading atmospheric noise suppression performance. Wavelet denoising and median filtering are the optimal methods among existing solutions. However, due to the extremely low transmission rate of ultra-low frequency signals and the limited number of effective input bits, the performance improvement is not significant. Furthermore, if only MSK modulation is used, the impact of inter-symbol interference is substantial.

[0007] Therefore, to address the aforementioned problems in existing technologies, a method combining SCIFDMA system architecture MSK modulation with a specific limiter is introduced to eliminate them. The main purpose is...

[0008] 1. The entire system adopts the SCIFDMA system processing architecture, incorporating multiple carriers to increase the correlation between symbols and reduce inter-symbol interference. Furthermore, using subcarriers to carry the signal effectively protects the signal waveform, enhancing noise immunity and facilitating signal demodulation and bit error rate control. Combined with coding and spread spectrum techniques, it effectively achieves anti-interference goals.

[0009] 2. By using power scaling in signal processing, a portion of the noise power is converted into signal power, thus relatively reducing noise energy and minimizing interference with the signal. Furthermore, the power of the effective information is relatively increased, enabling more effective decoding and improving system performance. Summary of the Invention

[0010] The purpose of this invention is to provide an ultra-low frequency atmospheric noise cancellation system, method, and apparatus. First, a portion of the noise power in the time-domain signal is converted into signal power, thereby relatively reducing the noise energy of the time-domain signal. Then, the time-domain signal is filtered. Next, the time-domain signal is converted into a frequency-domain signal to eliminate noise, and then converted back into a time-domain signal, which facilitates effective decoding and relatively increases the power of the effective information.

[0011] The technical solution for achieving the objective of this invention is as follows:

[0012] On one hand, the present invention provides an ultra-low frequency atmospheric noise cancellation system, comprising:

[0013] The data preprocessing module preprocesses the time-domain signal by scaling a portion of the noise power of the time-domain signal to eliminate most of the noise in the time-domain signal, thereby obtaining an ultra-low frequency noise-cancelled time-domain signal.

[0014] A first data processing module is connected to the data preprocessing module. The first data processing module filters the ultra-low frequency primary noise cancellation time-domain signal to obtain an ultra-low frequency secondary noise cancellation time-domain signal.

[0015] The second data processing module is connected to the first data processing module. The second data processing module converts the ultra-low frequency secondary noise cancellation time-domain signal into a frequency-domain signal, processes the frequency-domain signal, and then converts it back to a time-domain signal to obtain the ultra-low frequency atmospheric noise cancellation signal.

[0016] Based on one aspect, in one embodiment of the present invention, the data preprocessing module includes:

[0017] A power scaling module performs power scaling on a time-domain signal to obtain a time-domain scaled signal.

[0018] Based on one aspect, in one embodiment of the present invention, the first data processing module includes:

[0019] A threshold clipper is connected to the power scaling module. The threshold clipper compares the time-domain scaled signal with preset upper and lower thresholds. The ultra-low frequency secondary noise cancellation time-domain signal output by the threshold clipper is limited between the upper and lower thresholds.

[0020] Based on one aspect, in one embodiment of the present invention, the second data processing module includes:

[0021] The DFT module is connected to the first data processing module, and the DFT module converts the ultra-low frequency secondary noise cancellation time-domain signal from the time domain to the frequency domain.

[0022] A subcarrier demapping module is connected to the DFT module. The subcarrier demapping module is applied to the SCIFDMA system, which divides the ultra-low frequency secondary noise cancellation frequency domain signal into multiple subcarriers. The subcarrier demapping module demaps each subcarrier, converting the frequency domain to the time domain.

[0023] The MSK modulation module is connected to the subcarrier demapping module, and the MSK modulation module demodulates the subcarrier time-domain signal.

[0024] Based on one aspect, in one embodiment of the present invention, it further includes:

[0025] The receiving module receives the time-domain signal sent by the transmitting module and transmits the time-domain signal to the data preprocessing module.

[0026] The receiving module and the transmitting module transmit signals through a channel.

[0027] Based on one aspect, in one embodiment of the present invention, it further includes:

[0028] An encoding module is used to encode input data, wherein the encoding module processes the input data into encoded data;

[0029] A third data processing module for processing encoded data into a time-domain signal, wherein the input of the third data processing module is connected to the encoding module and the output of the third data processing module is connected to the receiving module.

[0030] Based on one aspect, in one embodiment of the present invention, it further includes:

[0031] A synchronization module is connected to the receiving module, which correctly locates the frame position of the time-domain signal; the synchronization module is also connected to the data preprocessing module, which preprocesses the time-domain signal after the frame position begins.

[0032] In digital communication, digital signals typically contain data and control information for identification and verification. Digital signals are transmitted in a series of frames. The role of the synchronization module is to correctly identify the start position of a frame at the receiving end for proper decoding and processing. It determines the frame boundaries by detecting frame synchronization signals or specific frame header identifiers. Once the start position of a frame is determined, the receiving end can decode and process the data according to predetermined formats and rules.

[0033] On the other hand, the present invention provides a method for eliminating ultra-low frequency atmospheric noise, comprising the following steps:

[0034] By scaling a portion of the noise power of the time-domain signal to eliminate most of the noise in the time-domain signal, an ultra-low frequency noise-cancelled time-domain signal is obtained.

[0035] The time-domain signal of the first-order noise cancellation of ultra-low frequency is filtered to obtain the time-domain signal of the second-order noise cancellation of ultra-low frequency.

[0036] The ultra-low frequency secondary noise cancellation time-domain signal is converted into a frequency-domain signal, and the frequency-domain signal is processed and then converted back into a time-domain signal to obtain the ultra-low frequency atmospheric noise cancellation signal.

[0037] On the other hand, in one embodiment of the present invention, the following steps are also included:

[0038] Process the input data into encoded data;

[0039] Process the encoded data to obtain a time-domain signal;

[0040] The receiving module receives the time-domain signal sent by the transmitting module;

[0041] Correctly locate the frame position of the time-domain signal and preprocess the time-domain signal after the start of the frame position.

[0042] In another aspect, the present invention provides an ultra-low frequency atmospheric noise cancellation device, based on the above-mentioned ultra-low frequency atmospheric noise cancellation system.

[0043] Compared with the prior art, the beneficial effects of the present invention are:

[0044] 1. This invention first converts a portion of the noise power in the time-domain signal into signal power, thereby relatively reducing the noise energy of the time-domain signal. Then, the time-domain signal is filtered. Next, the time-domain signal is converted to a frequency-domain signal to eliminate noise before being converted back to a time-domain signal, which facilitates effective decoding and relatively increases the power of the effective information.

[0045] 2. This invention processes the time-domain signal in the input threshold clipper. When the amplitude of the input time-domain signal exceeds the upper threshold, the amplitude of the output signal is limited to the upper threshold; when the amplitude of the input time-domain signal is lower than the lower threshold, the amplitude of the output signal is limited to the lower threshold, thus achieving noise cancellation in one step. Attached Figure Description

[0046] Figure 1 A principle block diagram of an ultra-low frequency atmospheric noise cancellation system provided by the present invention;

[0047] Figure 2A schematic diagram of an ultra-low frequency atmospheric noise cancellation system provided by the present invention;

[0048] Figure 3 A flowchart of an ultra-low frequency atmospheric noise elimination method provided by the present invention;

[0049] Figure 4 A simplified flowchart of an ultra-low frequency atmospheric noise elimination method provided by the present invention;

[0050] Figure 5 This is a time-domain waveform of the signal before power scaling in this invention;

[0051] Figure 6 The signal time-domain waveform after power scaling according to this invention;

[0052] Figure 7 This is a comparison chart of the performance of different modulation methods for eliminating atmospheric noise at ultra-low frequencies in simulation experiments;

[0053] Figure 8 This is a performance comparison chart between the proposed solution and similar solutions in a simulation experiment. Detailed Implementation

[0054] The present invention will now be described in detail with reference to the embodiments shown in the accompanying drawings. However, it should be noted that these embodiments are not intended to limit the present invention. Equivalent changes or substitutions in function, method, or structure made by those skilled in the art based on these embodiments are all within the scope of protection of the present invention.

[0055] Please see Figure 1 , Figure 1 This invention provides a principle block diagram of an ultra-low frequency atmospheric noise cancellation system. An embodiment of this invention provides an ultra-low frequency atmospheric noise cancellation system, comprising: an encoding module for encoding input data, a third data processing module for processing the encoded data into a time-domain signal, a receiving module, a synchronization module, a data preprocessing module, a first data processing module, and a second data processing module, wherein:

[0056] The encoding module processes the input data into encoded data. Please refer to [link / reference]. Figure 2 , Figure 2 This is a schematic diagram of an ultra-low frequency atmospheric noise cancellation system provided by the present invention. The encoding module of the present invention encodes the input data. The present invention uses Turbo encoding, mainly because Turbo codes have strong error correction capabilities, which can effectively correct bit errors generated during channel transmission, and have anti-interference and anti-fading capabilities, thereby improving the reliability of the communication system.

[0057] The input of the third data processing module is connected to the encoding module, and the output of the third data processing module is connected to the receiving module. Please continue reading. Figure 2 , Figure 2 The schematic diagram of an ultra-low frequency atmospheric noise cancellation system provided by this invention shows the following processing steps of the third data processing module in this embodiment: The encoded data undergoes block interleaving, primarily to resist channel time-varying characteristics and improve signal anti-interference capabilities. This is achieved by rearranging the data, changing its temporal distribution, and reducing the probability of consecutive errors. The interleaved data is then spread spectrum; spread spectrum technology can improve its anti-interference capability and also widen the bandwidth. The spread spectrum data is then modulated using MSK (Minimum Frequency Shift Keying). MSK modulation has several advantages, including high spectral efficiency, strong anti-interference capability, low inter-symbol interference impact, and simple implementation. The modulated data is first converted to the frequency domain, then pilot signals are added, subcarriers are mapped, and the data is converted to the time domain. A cyclic prefix is ​​then added, primarily to reduce inter-symbol interference. After generating a synchronization header of a certain length, the data is framed and sent out.

[0058] The receiving module receives the time-domain signal sent by the transmitting module and transmits the time-domain signal to the data preprocessing module; the receiving module and the transmitting module transmit signals through the channel.

[0059] The synchronization module connects to the receiving module, ensuring the correct location of the frame in the time domain signal. It also connects to the data preprocessing module, which preprocesses the time domain signal following the start of the frame. In digital communication, digital signals typically contain data and control information for identification and verification. These signals are transmitted in a series of frames. The synchronization module's role is to correctly identify the start of the frame at the receiving end for proper decoding and processing. It determines the frame boundaries by detecting frame synchronization signals or specific frame header identifiers. Once the start of the frame is determined, the receiving end can decode and process the data according to predetermined formats and rules.

[0060] The data preprocessing module preprocesses the time-domain signal, scaling down a portion of the noise power in the time-domain signal to eliminate most of the noise, resulting in an ultra-low frequency, single-stage noise-cancelled time-domain signal. This data preprocessing module includes a power scaling module, which scales the power of the time-domain signal to obtain a scaled time-domain signal. Please continue reading... Figure 2 , Figure 2This invention provides a schematic diagram of an ultra-low frequency atmospheric noise cancellation system. In this embodiment, the power scaling module increases the signal power to compete with the noise power, thus better separating the signal and noise. In practical applications, the receiving module first performs synchronization to correctly locate the frame position. Due to the large amplitude of impulse noise, DC offset removal and median filtering are performed before synchronization to better locate the start of the data. After confirming the data frame, the data preprocessing module first preprocesses the data, converting a portion of the noise power into signal power.

[0061] The first data processing module is connected to the data preprocessing module. This module filters the ultra-low frequency (ULF) primary noise-cancelled time-domain signal to obtain an ULF secondary noise-cancelled time-domain signal. This first data processing module includes a threshold clipper connected to the power scaling module. The threshold clipper compares the time-domain scaled signal with preset upper and lower thresholds, limiting the ULF secondary noise-cancelled time-domain signal output by the threshold clipper to between the upper and lower thresholds. Please continue reading. Figure 2 , Figure 2 This invention provides a schematic diagram of an ultra-low frequency atmospheric noise cancellation system. In this embodiment, the threshold clipper is a non-linear processing method. Its purpose is to set the portion of noise below a preset threshold to zero, thereby reducing the impact of noise on the signal. Setting different thresholds is to avoid discarding valid information. In practical applications, the receiving module first performs synchronization to correctly locate the frame position. Due to the relatively large amplitude of impulse noise, DC offset removal and median filtering are performed before synchronization to better locate the start of the data. After confirming the data frame, the data preprocessing module first preprocesses the data, converting a portion of the noise power into signal power. Then, the threshold clipper performs a threshold limiting clipper for filtering.

[0062] The second data processing module is connected to the first data processing module. The second data processing module converts the ultra-low frequency (UHF) secondary noise cancellation time-domain signal into a frequency-domain signal, processes the frequency-domain signal, and then converts it back to the time-domain signal to obtain the UHF atmospheric noise cancellation signal. The aforementioned second data processing module includes a DFT (Discrete Fourier Transform) module, a subcarrier demapping module, and an MSK modulation module. The DFT module is connected to the first data processing module and converts the UHF secondary noise cancellation time-domain signal from the time domain to the frequency domain. The subcarrier demapping module is connected to the DFT module and is applied to the SCIFDMA system. The SCIFDMA system divides the UHF secondary noise cancellation frequency-domain signal into multiple subcarriers. The subcarrier demapping module demaps each subcarrier, converting the frequency domain to the time domain. The MSK modulation module is connected to the subcarrier demapping module and demodulates the subcarrier time-domain signal. Please continue reading. Figure 2 , Figure 2 This invention provides a schematic diagram of an ultra-low frequency atmospheric noise cancellation system. In practical applications, the receiving module first performs synchronization to correctly locate the frame position. Due to the relatively large amplitude of impulse noise, DC offset removal and median filtering are performed before synchronization to better locate the start of the data. After confirming the data frame, the power scaling module first preprocesses the data, converting a portion of the noise power into signal power. Then, a threshold clipper performs a threshold limiting clipper for filtering. Subsequently, the DFT module, subcarrier demapping module, and MSK modulation module perform demapping, DFT filtering estimation, MMSE equalization, and other operations in the frequency domain. The equalized data is converted to the time domain and then demodulated, deinterleaved, and decoded. This embodiment of the invention uses a combination of parameter estimation and iterative decoding. Finally, the decoded data is compared with the input data to determine the error rate performance.

[0063] This invention employs a combination of power scaling and a threshold clipper to allocate a portion of the noise power to the signal. Furthermore, the threshold clipper in this embodiment sets a suitable threshold (greater than the magnitude of the effective signal), treating noise values ​​above the threshold as atmospheric noise and converting this energy into signal power. This prevents effective information from being swallowed by noise due to insufficient power, thus avoiding poor performance. After this initial signal processing, a clipper is added to further filter out large-amplitude noise.

[0064] Please see Figure 3 , Figure 3 This invention provides a method for eliminating ultra-low frequency atmospheric noise, comprising the following steps: (Flowchart shown)

[0065] Process the input data into encoded data;

[0066] Process the encoded data to obtain a time-domain signal;

[0067] The receiving module receives the time-domain signal sent by the transmitting module;

[0068] Correctly locate the frame position of the time-domain signal and preprocess the time-domain signal after the start of the frame position;

[0069] By scaling a portion of the noise power of the time-domain signal to eliminate most of the noise in the time-domain signal, an ultra-low frequency noise-cancelled time-domain signal is obtained.

[0070] The time-domain signal of the first-order noise cancellation of ultra-low frequency is filtered to obtain the time-domain signal of the second-order noise cancellation of ultra-low frequency.

[0071] The ultra-low frequency secondary noise cancellation time-domain signal is converted into a frequency-domain signal, and the frequency-domain signal is processed and then converted back into a time-domain signal to obtain the ultra-low frequency atmospheric noise cancellation signal.

[0072] For more details, please see Figure 2 and Figure 3 , Figure 2 This is a schematic diagram illustrating the principle of an ultra-low frequency atmospheric noise cancellation system. Figure 3This is a flowchart of an ultra-low frequency atmospheric noise cancellation method. In this embodiment of the invention, input data is encoded. Turbo coding is used primarily because Turbo codes have strong error correction capabilities, effectively correcting bit errors generated during channel transmission, and possess anti-interference and anti-fading capabilities, thereby improving the reliability of the communication system. The encoded data undergoes block interleaving, mainly to resist the time-varying nature of the channel and improve the signal's anti-interference capability. It reduces the probability of consecutive errors by rearranging the data and changing its temporal distribution. The interleaved data is then spread spectrum; spread spectrum technology can improve its anti-interference capability and also widen the bandwidth. The spread spectrum data is then subjected to MSK modulation. MSK modulation has several advantages, including high spectral efficiency, strong anti-interference capability, low inter-symbol interference impact, and simple implementation. The modulated data is first converted to the frequency domain, then pilot signals are added, subcarrier mapping is performed, and then it is converted to the time domain. A cyclic prefix is ​​then added, mainly to reduce inter-symbol interference. After generating a synchronization header of a certain length, the data is framed and sent out. The receiving end first performs synchronization to correctly locate the frame position. Due to the relatively large amplitude of impulse noise, DC offset removal and median filtering are performed before synchronization to better locate the start of the data. After confirming the data frame, the data is preprocessed to convert some noise power into signal power. Then, a threshold clipping filter is used for filtering. Following this, demapping, DFT filtering estimation, and MMSE equalization are performed in the frequency domain. The equalized data is then converted to the time domain and subjected to demodulation, deinterleaving, and decoding. This invention uses a combination of parameter estimation and iterative decoding. Finally, the decoded data is compared with the incoming data to determine the error rate performance.

[0073] This invention employs a SCIFDMA (Single-carrier Frequency-Division Multiple Access) system to carry the signal on a carrier, combined with MSK modulation. More specifically, this invention transforms the modulated signal into the frequency domain through DFT precoding, distributing energy across multiple subcarriers. This reduces the peak-to-average power ratio (PAPR). The frequency domain is then mapped onto the subcarriers before being converted back to the time domain for subsequent operations. In this invention, the DFT precoding points are 64, and the IFFT (Inverse Fast Fourier Transform) points are 128. Since both the IFFT and DFT points are powers of 2, the output signal is a single-carrier signal, further reducing the PAPR and minimizing in-band and out-of-band interference.

[0074] This invention employs a combination of power scaling and threshold clipping to eliminate atmospheric impulse noise during signal processing. After synchronization and data frame acquisition, the noise power is extremely high, affecting signal resolution. Therefore, a power scaling step is performed first to convert a portion of the noise power into signal power. The processing procedure is as follows: First, a power threshold is set. Positions and values ​​exceeding this threshold are extracted, their total power is calculated, and the calculated power is used to normalize the overall signal. Then, the result is multiplied by the square root of the threshold.

[0075] It should be noted that for an embodiment of the present invention, a method for eliminating ultra-low frequency atmospheric noise, please refer to [link to relevant documentation]. Figure 4 , Figure 4 This is a simplified flowchart of an ultra-low frequency atmospheric noise cancellation method. Clipping only processes values ​​that do not meet the conditions, ensuring noise cancellation without damaging the signal. In this embodiment, the modulated signal is transformed to the frequency domain through DFT precoding, distributing energy across multiple subcarriers, which reduces the peak-to-average power ratio (PAPR). The frequency domain is then mapped to the subcarriers before being converted back to the time domain for subsequent operations. In this embodiment, the DFT precoding points are 64, and the IFFT points are 128. Since both the IFFT and DFT points are powers of 2, the output signal is a single-carrier signal, further reducing the PAPR and minimizing in-band and out-of-band interference. Furthermore, after synchronization and data frame acquisition, the noise power is extremely high, affecting signal resolution. Therefore, a power scaling step is performed to convert a portion of the noise power into signal power. The following describes the processing procedure: First, set a power threshold, extract the positions and values ​​that exceed this threshold, calculate their total power, normalize the overall signal using the calculated power, and then multiply it by the square root of the threshold.

[0076] Compare the time-domain waveform diagram to... Figure 5 and Figure 6 As shown, Figure 5 The signal time-domain waveform before power scaling. Figure 6 This is the time-domain waveform of the signal after power scaling. Due to the excessive data length, Figure 5 and Figure 6 Only the first 10,000 points are drawn. Figure 6 As can be seen, most of the impulse noise has been eliminated. However, since the amplitude of the transmitted signal is 1, the impact of the impulse noise is still significant, so secondary filtering is still required. Here, a threshold clipper is used. If threshold clipping is not performed, under high signal-to-noise ratio conditions and when the signal power is good, some signal power may be lost, leading to a deterioration in performance.

[0077] Furthermore, embodiments of the present invention provide an ultra-low frequency atmospheric noise cancellation device, based on the aforementioned ultra-low frequency atmospheric noise cancellation system.

[0078] The following simulation comparison will be conducted. First, the method for eliminating atmospheric noise will be fixed (using a combination of power limiting and threshold clipping). Then, the performance of different systems under different modulation methods will be compared. Please refer to [link to simulation]. Figure 7 , Figure 7 This is a comparison chart of the performance of different modulation methods for eliminating atmospheric noise at ultra-low frequencies in a simulation experiment. Figure 7 Simulations of the bit error rate curves for OFDM / SCFDE / SCIFDMA systems combined with QPSK / MSK modulation respectively show that the SCIFDMA system outperforms the other two systems, and MSK modulation performs better than QPSK (Quadrature Phase Shift Keying) modulation. Therefore, compared with existing modulation methods, the ultra-low frequency atmospheric noise cancellation system, method, and apparatus of this invention have greater performance advantages.

[0079] Next, using a fixed modulation scheme combining SCIFDMA and MSK, the performance of different impulse noise cancellation methods is compared. Among these methods, limiters, nullers, clippers, and wavelet denoising combined with median filtering are commonly used in current research. The combination of wavelet denoising and median filtering shows the best performance among these methods. However, the ultra-low frequency atmospheric noise cancellation system, method, and apparatus proposed in this invention, which combines power scaling with threshold clipping, exhibits stronger applicability in ultra-low frequency systems and achieves a 6dB performance improvement compared to existing methods.

[0080] Finally, a comparison was made with similar methods, employing a combination of MSK modulation and a whitening filter. Spread spectrum was also used for interference suppression, and a Rake receiver was used for equalization. Please refer to [link / reference]. Figure 8 , Figure 8 This is a performance comparison chart between the proposed solution and similar solutions in simulation experiments. Figure 8 Simulations of similar methods show that the performance of this method is far superior to that of similar methods, with an improvement of approximately 6dB.

[0081] The following is about Figure 8 The similar solutions are detailed below:

[0082] The similar scheme uses a joint suppression algorithm, which is a combination of MSK modulation and whitening filter. The processing flow of this similar scheme is as follows: First, the MSK modulated signal after adding impulse noise is processed by the whitening filter; then, based on the data after interference suppression, the parameters of the impulse noise are estimated and its amplitude PDF is calculated; next, PZMNL is designed to obtain the optimal nonlinear transformation; finally, the signal after interference suppression is transformed by PZMNL and then matched filtering is applied for detection. The similar scheme has the following potential disadvantages: (1) The whitening filter used in data processing may introduce additional computational complexity and delay, and the performance controllability is too small. (2) The signal after interference suppression is exchanged by PZMNL and a matched filter is applied for detection. However, the design and parameter selection of PZMNL are crucial to the system performance. If the selection is inappropriate, it will lead to signal distortion and decoding errors. (3) The algorithm involves multiple processing steps, including filtering, parameter estimation, nonlinear transformation and matched filtering, which will bring high computational complexity.

[0083] The present invention is as follows Figure 2 The illustrated scheme employs the SCIFDMA system architecture. The SCIFDMA system boasts the lowest peak-to-average power ratio (PAPR), effectively improving the terminal's transmission efficiency. Furthermore, the SCIFDMA system utilizes frequency-domain equalization technology to address frequency-selective fading. It combines the system capacity and multiple access capabilities of the OFDMA system, and its complexity is lower than that of single-carrier time-domain equalization methods. Its key feature is the addition of pilot signals in the frequency domain to achieve frequency-domain equalization, thus achieving superior equalization results with lower complexity. This embodiment of the invention introduces frequency-domain pilot signaling and subcarrier mapping into the basic system, and similar to the SCFDE system, it can perform frequency-domain equalization.

[0084] The detailed descriptions listed above are merely specific descriptions of feasible embodiments of the present invention, and are not intended to limit the scope of protection of the present invention. All equivalent embodiments or modifications made without departing from the spirit of the present invention should be included within the scope of protection of the present invention.

[0085] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0086] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. An ultra-low frequency atmospheric noise cancellation system, characterized in that, include: The data preprocessing module preprocesses the time-domain signal by scaling a portion of the noise power of the time-domain signal to eliminate most of the noise in the time-domain signal, thereby obtaining an ultra-low frequency noise-cancelled time-domain signal. The data preprocessing module includes a power scaling module, which is used to perform power scaling on the time-domain signal to obtain a time-domain scaled signal. The step of power scaling the time-domain signal to obtain a time-domain scaled signal includes: Set a power threshold, extract the positions in the time domain signal whose amplitude is greater than the power threshold, extract the amplitude values ​​corresponding to each position, calculate the power sum of all the extracted amplitude values, normalize the time domain signal based on the power sum, and then multiply the normalized time domain signal by the square root of the power threshold to obtain the time domain scaled signal. A first data processing module is connected to the data preprocessing module. The first data processing module filters the ultra-low frequency primary noise cancellation time-domain signal to obtain an ultra-low frequency secondary noise cancellation time-domain signal. The first data processing module includes a threshold clipper connected to the data preprocessing module. The threshold clipper is used to compare the time-domain scaled signal with preset upper and lower thresholds. The ultra-low frequency secondary noise cancellation time-domain signal output by the threshold clipper is limited between the upper and lower thresholds. The second data processing module is connected to the first data processing module. The second data processing module converts the ultra-low frequency secondary noise cancellation time-domain signal into a frequency-domain signal, processes the frequency-domain signal, and then converts it back to a time-domain signal to obtain the ultra-low frequency atmospheric noise cancellation signal.

2. The ultra-low frequency atmospheric noise cancellation system according to claim 1, characterized in that, The second data processing module includes: The DFT module is connected to the first data processing module, and the DFT module converts the ultra-low frequency secondary noise cancellation time-domain signal from the time domain to the frequency domain. A subcarrier demapping module is connected to the DFT module. The subcarrier demapping module is applied to the SCIFDMA system, which divides the ultra-low frequency secondary noise cancellation frequency domain signal into multiple subcarriers. The subcarrier demapping module demaps each subcarrier, converting the frequency domain to the time domain. The MSK modulation module is connected to the subcarrier demapping module, and the MSK modulation module demodulates the subcarrier time-domain signal.

3. A low-frequency atmospheric noise cancellation system according to any one of claims 1 and 2, characterized in that, Also includes: The receiving module receives the time-domain signal sent by the transmitting module and transmits the time-domain signal to the data preprocessing module.

4. The ultra-low frequency atmospheric noise cancellation system according to claim 3, characterized in that, Also includes: An encoding module is used to encode input data, wherein the encoding module processes the input data into encoded data; A third data processing module for processing encoded data into a time-domain signal, wherein the input of the third data processing module is connected to the encoding module and the output of the third data processing module is connected to the receiving module.

5. The ultra-low frequency atmospheric noise cancellation system according to claim 3, characterized in that, Also includes: A synchronization module is connected to the receiving module, which correctly locates the frame position of the time-domain signal; the synchronization module is also connected to the data preprocessing module, which preprocesses the time-domain signal after the frame position begins.

6. A method for eliminating ultra-low frequency atmospheric noise, characterized in that, The ultra-low frequency atmospheric noise cancellation system according to any one of claims 1-5 includes the following steps: By scaling a portion of the noise power of the time-domain signal to eliminate most of the noise in the time-domain signal, an ultra-low frequency noise-cancelled time-domain signal is obtained. The time-domain signal of the first-order noise cancellation of ultra-low frequency is filtered to obtain the time-domain signal of the second-order noise cancellation of ultra-low frequency. The ultra-low frequency secondary noise cancellation time-domain signal is converted into a frequency-domain signal, and the frequency-domain signal is processed and then converted back into a time-domain signal to obtain the ultra-low frequency atmospheric noise cancellation signal.

7. The method for eliminating ultra-low frequency atmospheric noise according to claim 6, characterized in that, It also includes the following steps: Process the input data into encoded data; Process the encoded data to obtain a time-domain signal; The receiving module receives the time-domain signal sent by the transmitting module; Correctly locate the frame position of the time-domain signal and preprocess the time-domain signal after the start of the frame position.

8. A device for eliminating ultra-low frequency atmospheric noise, characterized in that, An ultra-low frequency atmospheric noise cancellation system according to any one of claims 1-5.

Images