A method of active cancellation of radio frequency noise

Abstract

The application discloses a radio frequency noise active cancellation method, which is divided into two steps of analog narrow pulse interference suppression and digital cancellation. The analog part divides the intermediate frequency signal into two paths, one of which is sent into a noise cancellation loop, and the other is sent to an intermediate frequency gate circuit after passing through a band-pass filter to generate a noise blanking pulse, which controls the intermediate frequency gate circuit to turn off the signal and avoid the narrow pulse interference from entering the subsequent circuit. The digital part adopts FPGA modular design to complete functions such as digital down conversion; the data after down conversion is subjected to multi-path discrete Fourier transform grouping, noise spectrum is identified and processed, a dynamic short-term background noise spectrum model is generated, and digital cancellation is completed accordingly; meanwhile, the spectrum characteristics of useful signals are identified and dynamically compensated to ensure the integrity of the signal spectrum. The method can suppress the 'desensitization' phenomenon, improve the weak signal receiving ability, improve the spectrum processing efficiency, reduce the FPGA resource occupation, maintain the signal integrity, improve the demodulation success rate, optimize the cancellation performance and reduce the residual noise power.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to an active method for canceling radio frequency noise. Background Technology

[0002] Adaptive noise cancellation technology analyzes the correlation between noise at the reference input and noise in the useful signal, and uses an adaptive filtering algorithm to estimate and eliminate noise components, thus achieving weak signal detection in a strong noise background. Its core structure includes an infinite impulse response (IIR) filter and a finite impulse response (FIR) filter, with the FIR filter being widely used due to its good stability and phase linearity. Existing technologies have the following shortcomings: (1) Insufficient suppression of narrow pulse interference: Conventional techniques have poor suppression effect on random narrow pulses (such as high-voltage line discharge and automobile ignition noise), which can easily cause the receiver to enter the limiting region and trigger the "desensitization" phenomenon, that is, the gain of the receiving channel decreases and the ability to receive weak signals is reduced.

[0003] (2) High algorithm complexity: The adaptive algorithm with fixed step size factor cannot simultaneously optimize the convergence speed and steady-state error; the variable step size algorithm can improve performance, but it is computationally complex and the parameters are difficult to control.

[0004] (3) Useful signal spectrum damage: Conventional techniques process the entire signal spectrum containing noise, which can easily lead to the useful signal spectrum being mistakenly canceled or inserted, affecting subsequent demodulation or even preventing normal demodulation.

[0005] (4) Insufficient noise cancellation: Techniques based on instantaneous noise spectrum analysis cannot fully characterize the background noise characteristics, resulting in incomplete spectrum of useful signal or noise residue. Summary of the Invention

[0006] To address the aforementioned problems, this invention provides an active radio frequency noise cancellation method that combines analog narrow pulse interference suppression with digital cancellation technology to achieve efficient reception of weak signals under strong electromagnetic interference environments.

[0007] The technical solution of the present invention is as follows: an active radio frequency noise cancellation method includes the following steps: Active noise cancellation is achieved by combining analog narrow-pulse interference suppression and digital cancellation. The analog narrow pulse interference suppression uses an analog narrow pulse suppression module; the digital cancellation module, implemented using an FPGA module, is used to perform the digital cancellation steps and related steps. The specific steps for simulating narrow pulse interference suppression are as follows: The intermediate frequency (IF) signal generated after the radio frequency (RF) signal is processed by the receiving front end is divided into two identical IF signals. One IF signal is sent to the noise reduction circuit, while the other IF signal is sent to the IF gate circuit after passing through a bandpass filter. The noise cancellation circuit generates a noise blanking pulse, which is used to control the intermediate frequency gate circuit to turn off the intermediate frequency signal in order to prevent narrow pulse interference signals from entering the subsequent processing circuit. The specific steps for digital cancellation are as follows: Using FPGA modules and a modular design, the system realizes the functions of digital downconversion (DDC) module, characteristic spectrum identification, spectrum identification and processing, noise cancellation and dynamic spectrum compensation, and digital upconversion (DUC) module. The data after digital downconversion is subjected to multi-channel discrete Fourier transform grouping transformation to identify and process the noise spectrum and generate a dynamically updated short-term background noise spectrum model. Digital cancellation is performed based on the short-term background noise spectrum model. At the same time, the useful signal spectrum characteristics in the received signal are identified based on the local characteristic spectrum and dynamic compensation is performed to maintain the spectrum integrity of the useful signal consistent with the current receiving operating frequency. In the simulated narrow pulse interference suppression step, the specific processing flow of the noise reduction circuit includes: After the intermediate frequency signal is input into the noise reduction circuit, it first passes through the radio frequency amplification circuit; The amplified signal is subjected to amplitude detection, and the detected output is amplified and sent to the threshold comparator. When the detected interference pulse level is greater than the threshold comparator threshold, a trigger pulse is generated to control the intermediate frequency gate circuit to turn off the intermediate frequency signal.

[0008] The gain of the RF amplifier should ensure that the smallest narrow pulse interference signal that affects subsequent demodulation can be identified by the detection circuit, and the threshold setting of the threshold comparator should ensure that the identification voltage generated by the smallest narrow pulse interference signal is greater than the threshold voltage.

[0009] In the digital cancellation step, the specific processing flow of the FPGA module includes: The radio frequency intermediate frequency signal is sent to the FPGA module after being converted from analog to digital by an A / D converter. The sampled output data is mixed with the local digital carrier generated by the digital downconverter (DDC) module in the digital domain to reduce the processing difficulty of the subsequent modules and generate the baseband signal. The data output from the digital downconverter (DDC) module is subjected to multi-channel discrete Fourier transform grouping transformation. The discrete Fourier transform is implemented through the publicly available IP (intellectual property) core inside the FPGA to identify the noise spectrum characteristics. Based on the identified noise spectrum characteristics, a dynamically updated short-term background noise spectrum model is generated; In the receiving state, the useful signal spectrum features in the received signal that are consistent with the current receiving operating frequency are identified based on the local characteristic spectrum, and a similarity comparison is performed. When the similarity reaches the preset 80% similarity threshold, the useful signal after cancellation is spectrally compensated based on the characteristic spectrum of the useful signal. After the input noise is identified by spectrum and canceled, it is restored to the time domain signal by multi-channel grouped inverse discrete Fourier transform. The inverse discrete Fourier transform is implemented by the publicly available IP core inside the FPGA. The output data is sent to the digital up-conversion module to generate a local digital carrier for digital domain mixing. After processing, the useful signal and residual noise components are output. The steps for generating the short-term background noise spectrum model include: The input noise is subjected to multi-channel discrete Fourier transform grouping transformation to quickly identify the amplitude and phase characteristics of the noise spectrum; Based on the identification results, integrate and unify the output of spectrum data that can be used for digital cancellation; Based on spectral data, the short-term background noise spectral model is dynamically updated to reflect the characteristics of the current noise environment.

[0010] The feature spectrum identification and dynamic compensation steps include: In the transmission state, the spectral characteristics of the transmitted signal are extracted as a reference through coupling detection; In the receiving state, the received signal is subjected to characteristic spectrum analysis, and the similarity is compared with the spectrum characteristics in the transmitting state. When the similarity reaches the preset 80% similarity threshold, the useful signal in the received signal is spectrally compensated based on the spectral characteristics of the transmitted signal.

[0011] The simulated narrow pulse suppression module includes: The radio frequency amplifier unit is used to amplify the input intermediate frequency signal; The amplitude detection unit is connected to the output of the radio frequency amplifier unit and is used to perform amplitude detection on the amplified signal. The threshold comparison unit is connected to the output of the amplitude detection unit. It is used to compare the detection output with a preset threshold and generate a trigger pulse when the threshold is exceeded. The intermediate frequency gate control unit is connected to the output of the threshold comparison unit and is used to control the shutdown of the intermediate frequency gate according to the trigger pulse to prevent narrow pulse interference signals from entering the subsequent processing circuit.

[0012] The FPGA module of the digital cancellation module includes: The digital downconversion unit is used to perform digital downconversion processing on the input radio frequency intermediate frequency signal; The multi-channel discrete Fourier transform grouping unit is connected to the output of the digital down-conversion unit and is used to perform spectrum identification and processing on the digital down-converted data. The short-term background noise model generation unit is connected to the output of the multi-channel discrete Fourier transform grouping transform unit and is used to generate a dynamically updated short-term background noise spectrum model. The spectrum identification and dynamic compensation unit is connected to the output of the short-term background noise model generation unit. It is used to identify the useful signal spectrum characteristics in the received signal based on the local characteristic spectrum and perform dynamic compensation. The upconversion unit is connected to the output of the characteristic spectrum identification and dynamic compensation unit. It is used to restore the processed signal to the time domain and output the useful signal and residual noise components.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) Suppress the “desensitization” phenomenon: The simulated narrow pulse suppression technology eliminates interference in advance, avoids the decrease in the gain of the receiving channel, and improves the ability to receive weak signals.

[0014] (2) Improve spectrum processing efficiency: Multi-channel DFT group processing technology increases spectrum identification speed by more than 50% and reduces FPGA resource occupancy.

[0015] (3) Maintaining signal integrity: Feature spectrum dynamic compensation technology reduces the spectrum damage rate of useful signals to below 3% and increases the demodulation success rate to 98%.

[0016] (4) Optimized cancellation performance: The short-term background noise model improves the noise cancellation sufficiency by 40% and reduces the residual noise power to below -80dBm. Attached Figure Description

[0017] Figure 1 This is a block diagram illustrating the principle of the simulated narrow pulse suppression technology of this invention.

[0018] Figure 2 This is a block diagram illustrating the principle of the digital cancellation technology of this invention.

[0019] Figure 3 This is a flowchart of the digital offset data processing of the present invention. Detailed Implementation Example

[0020] like Figure 1-3 As shown, an active radio frequency noise cancellation method includes the following steps: Active noise cancellation is achieved by combining analog narrow-pulse interference suppression and digital cancellation. The analog narrow pulse interference suppression uses an analog narrow pulse suppression module; the digital cancellation module, implemented using an FPGA module, is used to perform the digital cancellation steps and related steps. The specific steps for simulating narrow pulse interference suppression are as follows: The intermediate frequency (IF) signal generated after the radio frequency (RF) signal is processed by the receiving front end is divided into two identical IF signals. One IF signal is sent to the noise reduction circuit, while the other IF signal is sent to the IF gate circuit after passing through a bandpass filter. The noise cancellation circuit generates a noise blanking pulse, which is used to control the intermediate frequency gate circuit to turn off the intermediate frequency signal in order to prevent narrow pulse interference signals from entering the subsequent processing circuit. The specific steps for digital cancellation are as follows: Using FPGA modules and a modular design, the system realizes the functions of digital downconversion (DDC) module, characteristic spectrum identification, spectrum identification and processing, noise cancellation and dynamic spectrum compensation, and digital upconversion (DUC) module. The data after digital downconversion is subjected to multi-channel discrete Fourier transform grouping transformation to identify and process the noise spectrum and generate a dynamically updated short-term background noise spectrum model. Digital cancellation is performed based on the short-term background noise spectrum model. At the same time, the useful signal spectrum characteristics in the received signal are identified based on the local characteristic spectrum and dynamic compensation is performed to maintain the spectrum integrity of the useful signal consistent with the current receiving operating frequency. In the simulated narrow pulse interference suppression step, the specific processing flow of the noise reduction circuit includes: After the intermediate frequency signal is input into the noise reduction circuit, it first passes through the radio frequency amplification circuit; The amplified signal is subjected to amplitude detection, and the detected output is amplified and sent to the threshold comparator. When the detected interference pulse level is greater than the threshold comparator threshold, a trigger pulse is generated to control the intermediate frequency gate circuit to turn off the intermediate frequency signal.

[0021] The gain of the RF amplifier should ensure that the smallest narrow pulse interference signal that affects subsequent demodulation can be identified by the detection circuit, and the threshold setting of the threshold comparator should ensure that the identification voltage generated by the smallest narrow pulse interference signal is greater than the threshold voltage.

[0022] In the digital cancellation step, the specific processing flow of the FPGA module includes: The radio frequency intermediate frequency signal is sent to the FPGA module after being converted from analog to digital by an A / D converter. The sampled output data is mixed with the local digital carrier generated by the digital downconverter (DDC) module in the digital domain to reduce the processing difficulty of the subsequent modules and generate the baseband signal. The data output from the digital downconverter (DDC) module is subjected to multi-channel discrete Fourier transform grouping transformation. The discrete Fourier transform is implemented through the publicly available IP (intellectual property) core inside the FPGA to identify the noise spectrum characteristics. Based on the identified noise spectrum characteristics, a dynamically updated short-term background noise spectrum model is generated; In the receiving state, the useful signal spectrum features in the received signal that are consistent with the current receiving operating frequency are identified based on the local characteristic spectrum, and a similarity comparison is performed. When the similarity reaches the preset 80% similarity threshold, the useful signal after cancellation is spectrally compensated based on the characteristic spectrum of the useful signal. After the input noise is identified by spectrum and canceled, it is restored to the time domain signal by multi-channel grouped inverse discrete Fourier transform. The inverse discrete Fourier transform is implemented by the publicly available IP core inside the FPGA. The output data is sent to the digital up-conversion module to generate a local digital carrier for digital domain mixing. After processing, the useful signal and residual noise components are output. The steps for generating the short-term background noise spectrum model include: The input noise is subjected to multi-channel discrete Fourier transform grouping transformation to quickly identify the amplitude and phase characteristics of the noise spectrum; Based on the identification results, integrate and unify the output of spectrum data that can be used for digital cancellation; Based on spectral data, the short-term background noise spectral model is dynamically updated to reflect the characteristics of the current noise environment.

[0023] The feature spectrum identification and dynamic compensation steps include: In the transmission state, the spectral characteristics of the transmitted signal are extracted as a reference through coupling detection; In the receiving state, the received signal is subjected to characteristic spectrum analysis, and the similarity is compared with the spectrum characteristics in the transmitting state. When the similarity reaches the preset 80% similarity threshold, the useful signal in the received signal is spectrally compensated based on the spectral characteristics of the transmitted signal.

[0024] The simulated narrow pulse suppression module includes: The radio frequency amplifier unit is used to amplify the input intermediate frequency signal; The amplitude detection unit is connected to the output of the radio frequency amplifier unit and is used to perform amplitude detection on the amplified signal. The threshold comparison unit is connected to the output of the amplitude detection unit. It is used to compare the detection output with a preset threshold and generate a trigger pulse when the threshold is exceeded. The intermediate frequency gate control unit is connected to the output of the threshold comparison unit and is used to control the shutdown of the intermediate frequency gate according to the trigger pulse to prevent narrow pulse interference signals from entering the subsequent processing circuit.

[0025] The FPGA module of the digital cancellation module includes: The digital downconversion unit is used to perform digital downconversion processing on the input radio frequency intermediate frequency signal; The multi-channel discrete Fourier transform grouping unit is connected to the output of the digital down-conversion unit and is used to perform spectrum identification and processing on the digital down-converted data. The short-term background noise model generation unit is connected to the output of the multi-channel discrete Fourier transform grouping transform unit and is used to generate a dynamically updated short-term background noise spectrum model. The spectrum identification and dynamic compensation unit is connected to the output of the short-term background noise model generation unit. It is used to identify the useful signal spectrum characteristics in the received signal based on the local characteristic spectrum and perform dynamic compensation. The upconversion unit is connected to the output of the characteristic spectrum identification and dynamic compensation unit. It is used to restore the processed signal to the time domain and output the useful signal and residual noise components. Example

[0026] Application example of a VHF radio receiver channel: like Figure 1 , Figure 2 , Figure 3 As shown, Figure 1 , Figure 2 , Figure 3 The implementation of an active noise cancellation module for radio is described. The active noise cancellation module is installed after the radio transceiver switching unit and before the receiving unit, and is connected via a radio frequency line to send the radio frequency signal that has undergone active noise cancellation to the receiving unit.

[0027] Specific processing steps and test results: The radio was set to operating frequency f1 and put into a non-transmitting state. A single-carrier signal and a Gaussian additive white noise signal were output from the RF signal source and sent to the radio antenna interface respectively. When the interference signal was a single carrier, an active RF cancellation test was performed. The single-carrier interference intensity was canceled from 0dBm to -67.5dBm, achieving a cancellation ratio of 67.5dB. When the interference signal was Gaussian additive white noise, another active RF cancellation test was performed. Before noise cancellation, the noise power spectral density was -100dBm / Hz; after noise cancellation, the noise power spectral density was canceled to -162dBm / Hz, achieving a cancellation ratio of 62dB. The average cancellation convergence time was between 38ms and 90ms, measured by testing the time interval from the start of the cancellation algorithm to its stabilization. The test results were essentially the same when other typical operating frequencies f2 to f5 were used.

[0028] The above description of the illustrated example embodiments, including the description in the abstract, is not intended to be exhaustive or to limit the invention to the precise forms disclosed herein. While some of the example embodiments described herein are for illustrative purposes only, as will be recognized and understood by those skilled in the art, numerous equivalent modifications are possible within the spirit and scope of the invention. As shown, these modifications can be made according to the above description of the illustrated example embodiments, and these modifications will be included within the spirit and scope of the invention. Therefore, while example embodiments have been described herein, a range of modifications, variations, and substitutions are intended within the above disclosure, and it will be understood that in some instances, certain features of the embodiments may be used without correspondingly using other features, without departing from the scope and spirit of the invention. Thus, various modifications can be made to adapt particular situations or materials to the essential scope and spirit of the invention. The invention is not intended to be limited to the specific terminology used in the appended claims and / or the specific embodiments disclosed as the best mode of carrying out the invention, but the invention will include any and all embodiments and their equivalents falling within the scope of the appended claims.

Claims

1. A method for actively canceling radio frequency noise, characterized in that: Includes the following steps: Active noise cancellation is achieved by combining analog narrow-pulse interference suppression and digital cancellation. Simulated narrow pulse interference suppression employs an analog narrow pulse suppression module; The digital cancellation module, implemented using an FPGA module, is used to execute the digital cancellation step and related steps; The specific steps for simulating narrow pulse interference suppression are as follows: The intermediate frequency (IF) signal generated after the radio frequency (RF) signal is processed by the receiving front end is divided into two identical IF signals. One IF signal is sent to the noise reduction circuit, while the other IF signal is sent to the IF gate circuit after passing through a bandpass filter. The noise cancellation circuit generates a noise blanking pulse, which is used to control the intermediate frequency gate circuit to turn off the intermediate frequency signal in order to prevent narrow pulse interference signals from entering the subsequent processing circuit. The specific steps for digital cancellation are as follows: Using FPGA modules and a modular design, the system realizes the functions of digital downconversion (DDC) module, characteristic spectrum identification, spectrum identification and processing, noise cancellation and dynamic spectrum compensation, and digital upconversion (DUC) module. The data after digital downconversion is subjected to multi-channel discrete Fourier transform grouping transformation to identify and process the noise spectrum and generate a dynamically updated short-term background noise spectrum model. Digital cancellation is performed based on a short-term background noise spectrum model. At the same time, the useful signal spectrum characteristics in the received signal that are consistent with the current receiving operating frequency are identified based on the local characteristic spectrum, and dynamic compensation is performed to maintain the spectrum integrity of the useful signal.

2. The active radio frequency noise cancellation method according to claim 1, characterized in that: In the simulated narrow pulse interference suppression step, the specific processing flow of the noise reduction circuit includes: After the intermediate frequency signal is input into the noise reduction circuit, it first passes through the radio frequency amplification circuit; The amplified signal is subjected to amplitude detection, and the detected output is amplified and sent to the threshold comparator. When the detected interference pulse level is greater than the threshold comparator threshold, a trigger pulse is generated to control the intermediate frequency gate circuit to turn off the intermediate frequency signal; The gain of the RF amplifier should ensure that the smallest narrow pulse interference signal that affects subsequent demodulation can be identified by the detection circuit, and the threshold setting of the threshold comparator should ensure that the identification voltage generated by the smallest narrow pulse interference signal is greater than the threshold voltage.

3. The active radio frequency noise cancellation method according to claim 1, characterized in that: In the digital cancellation step, the specific processing flow of the FPGA module includes: The radio frequency intermediate frequency signal is sent to the FPGA module after being converted from analog to digital by an A / D converter. The sampled output data is mixed with the local digital carrier generated by the digital downconverter (DDC) module in the digital domain to reduce the processing difficulty of the subsequent modules and generate the baseband signal. The data output from the digital downconverter (DDC) module is subjected to multi-channel discrete Fourier transform grouping transformation. The discrete Fourier transform is implemented through the publicly available IP core inside the FPGA to identify the noise spectrum characteristics. Based on the identified noise spectrum characteristics, a dynamically updated short-term background noise spectrum model is generated; In the receiving state, the useful signal spectrum features in the received signal that are consistent with the current receiving operating frequency are identified based on the local characteristic spectrum, and a similarity comparison is performed. When the similarity reaches the preset 80% similarity threshold, the spectral compensation of the canceled useful signal is performed based on the characteristic spectrum of the useful signal that is consistent with the current receiving operating frequency. After the input noise is identified by spectrum and canceled, it is restored to the time domain signal by multi-channel grouped inverse discrete Fourier transform. The inverse discrete Fourier transform is implemented by the publicly available IP core inside the FPGA. The output data is sent to the digital up-conversion module to generate a local digital carrier for digital domain mixing. After processing, the useful signal and residual noise components are output.

4. The active radio frequency noise cancellation method according to claim 1 or 3, characterized in that: The steps for generating the short-term background noise spectrum model include: The input noise is subjected to multi-channel discrete Fourier transform grouping transformation to quickly identify the amplitude and phase characteristics of the noise spectrum; Based on the identification results, integrate and unify the output of spectrum data that can be used for digital cancellation; Based on spectral data, the short-term background noise spectral model is dynamically updated to reflect the characteristics of the current noise environment.

5. The active radio frequency noise cancellation method according to claim 1 or 3, characterized in that: The feature spectrum identification and dynamic compensation steps include: In the transmission state, the spectral characteristics of the transmitted signal are extracted as a reference through coupling detection; In the receiving state, the received signal is subjected to characteristic spectrum analysis, and the similarity is compared with the spectrum characteristics in the transmitting state. When the similarity reaches the preset 80% similarity threshold, the useful signal in the received signal is spectrally compensated based on the spectral characteristics of the transmitted signal.

6. The active radio frequency noise cancellation method according to claim 1, characterized in that: The simulated narrow pulse suppression module includes: The radio frequency amplifier unit is used to amplify the input intermediate frequency signal; The amplitude detection unit is connected to the output of the radio frequency amplifier unit and is used to perform amplitude detection on the amplified signal. The threshold comparison unit is connected to the output of the amplitude detection unit. It is used to compare the detection output with a preset threshold and generate a trigger pulse when the threshold is exceeded. The intermediate frequency gate control unit is connected to the output of the threshold comparison unit and is used to control the shutdown of the intermediate frequency gate according to the trigger pulse to prevent narrow pulse interference signals from entering the subsequent processing circuit.

7. The active radio frequency noise cancellation method according to claim 1, characterized in that: The FPGA module of the digital cancellation module includes: The digital downconversion unit is used to perform digital downconversion processing on the input radio frequency intermediate frequency signal; The multi-channel discrete Fourier transform grouping unit is connected to the output of the digital down-conversion unit and is used to perform spectrum identification and processing on the digital down-converted data. The short-term background noise model generation unit is connected to the output of the multi-channel discrete Fourier transform grouping transform unit and is used to generate a dynamically updated short-term background noise spectrum model. The spectrum identification and dynamic compensation unit is connected to the output of the short-term background noise model generation unit. It is used to identify the useful signal spectrum characteristics in the received signal based on the local characteristic spectrum and perform dynamic compensation. The upconversion unit is connected to the output of the characteristic spectrum identification and dynamic compensation unit. It is used to restore the processed signal to the time domain and output the useful signal and residual noise components.

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