CN220935173U - Short wave interference suppression system based on self-adaptive parameters - Google Patents
Short wave interference suppression system based on self-adaptive parameters Download PDFInfo
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Abstract
The utility model discloses a short wave interference suppression system based on self-adaptive parameters, which comprises an input module, a self-adaptive filter and an output module which are electrically connected in sequence, wherein the input module collects superposition signals of short wave signals and noise signals, the self-adaptive filter carries out filtering treatment on the superposition signals, and the output module outputs the filtered signals. According to the short wave interference suppression system disclosed by the utility model, the suppression of dynamic interference is realized through the self-adaptive parameter estimation algorithm, and the reliability and stability of short wave communication can be effectively improved. Meanwhile, the filter coefficient can be dynamically adjusted according to the actual running condition, so that the inhibition effect is further optimized.
Description
Technical Field
The utility model relates to the technical field of communication interference suppression, in particular to a short wave interference suppression system based on self-adaptive parameters in the field.
Background
Short-wave communication is receiving attention as an important long-distance communication mode. However, in practical application, since the propagation of the short wave signal is greatly affected by weather, topography, etc., it is easy to suffer from various interferences, such as electromagnetic interference, noise interference, etc., thereby affecting the communication quality and reliability.
Disclosure of utility model
The utility model aims to solve the technical problem of providing a short wave interference suppression system based on self-adaptive parameters.
In order to solve the technical problems, the utility model adopts the following technical scheme:
In a short wave interference suppression system based on adaptive parameters, the improvement comprising: the device comprises an input module, a self-adaptive filter and an output module which are electrically connected together in sequence, wherein the input module collects superposition signals of short wave signals and noise signals, the self-adaptive filter carries out filtering processing on the superposition signals, and the output module outputs the filtered signals.
Furthermore, the input module adopts a short wave signal receiving circuit.
Furthermore, the short wave signal receiving circuit adopts a superheterodyne receiving circuit or a direct conversion receiving circuit.
Further, the adaptive filter is a recursive filter.
Further, the adaptive filter is classified into a filter for suppressing the differential mode interference and a filter for suppressing the common mode interference.
Further, the adaptive filter comprises an adaptive parameter estimation module, a filter and a filter coefficient updating module, wherein the adaptive parameter estimation module is electrically connected with the input module and the filter respectively, the filter is electrically connected with the output module, and the filter coefficient updating module is electrically connected with the adaptive parameter estimation module and the filter respectively.
Further, the filter includes a band-pass filter, a notch filter, and a high-pass filter.
The beneficial effects of the utility model are as follows:
According to the short wave interference suppression system disclosed by the utility model, the suppression of dynamic interference is realized through the self-adaptive parameter estimation algorithm, and the reliability and stability of short wave communication can be effectively improved. Meanwhile, the filter coefficient can be dynamically adjusted according to the actual running condition, so that the inhibition effect is further optimized.
Drawings
FIG. 1 is a block diagram showing the circuit configuration of a short wave interference suppression system according to embodiment 1 of the present utility model;
FIG. 2 is a schematic diagram of the circuit configuration of a filter for suppressing differential mode interference;
FIG. 3 is a schematic diagram of the circuit configuration of a filter for suppressing common mode interference;
Fig. 4 is a flow chart of an adaptive parameter estimation algorithm.
Reference numerals: 1-input module, 2-adaptive filter, 21-adaptive parameter estimation module, 22-filter, 23-filter coefficient updating module and 3-output module.
Description of the embodiments
The present utility model will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present utility model more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the utility model.
In embodiment 1, as shown in fig. 1, the embodiment discloses a short wave interference suppression system based on adaptive parameters, which comprises an input module 1, an adaptive filter 2 and an output module 3 which are electrically connected together in sequence, wherein the input module collects superposition signals of short wave signals and noise signals, the adaptive filter carries out filtering processing on the superposition signals, and the output module outputs the filtered signals. The adaptive filter 2 comprises an adaptive parameter estimation module 21, a filter 22 and a filter coefficient updating module 23, wherein the adaptive parameter estimation module is electrically connected with the input module and the filter respectively, the filter is electrically connected with the output module, and the filter coefficient updating module is electrically connected with the adaptive parameter estimation module and the filter respectively.
In this embodiment, the input module employs a conventional short wave signal receiving circuit, such as a superheterodyne receiving circuit or a direct conversion receiving circuit. The adaptive filter is a recursive filter. The adaptive filter is classified into a filter for suppressing the differential mode interference shown in fig. 2 and a filter for suppressing the common mode interference shown in fig. 3. The filters include bandpass filters, notch (or rejection band) filters, and high pass filters. The input signal is first passed through a bandpass filter, which limits it to a certain frequency range. And then passed through a notch filter that selectively removes signals in a narrow frequency range. Finally, the signal is passed through a high pass filter, wherein signals below a certain frequency are suppressed and high frequency noise is preserved. Thus, short wave interference can be well suppressed, and interference noise in output signals can be greatly reduced.
The adaptive parameter estimation module can adopt a plurality of algorithms such as a wavelet analysis algorithm, an adaptive filter algorithm, a Kalman filtering algorithm and the like, wherein the wavelet analysis algorithm can effectively perform time-frequency domain analysis on signals, and has higher anti-interference performance and real-time performance; the adaptive filter algorithm can better adapt to signal change in a dynamic environment, but the shortwave signal has stronger nonlinear characteristics and needs to be optimized and improved; the Kalman filtering algorithm has higher precision and stability, and can obtain more accurate results when processing a large amount of data. Therefore, which algorithm is adopted specifically needs to be determined according to specific practical situations.
The filter coefficient updating module can adopt a plurality of algorithms such as a recursive least square method, an LMS algorithm, an RLS algorithm and the like, wherein the recursive least square method has higher convergence speed and stability, but consumes more calculation resources and storage space; the LMS algorithm has the advantages of simplicity, easiness, less calculated amount and the like, but the convergence speed is slower; the RLS algorithm can improve convergence speed and accuracy by dynamically adjusting parameters, but is complex to implement.
The output module may employ conventional digital signal processing algorithms, such as FFT conversion, filter design, demodulation, coding, etc., and may also perform secondary processing and processing on the signal as required by a particular application. For example, in communication, it is necessary to perform processing such as modulation, coding, and frequency modulation on signals, and in the fields of radar detection, geophysical prospecting, etc., it is necessary to perform processing such as pulse compression and doppler filtering on signals.
The working process of the short wave interference suppression system disclosed by the embodiment is as follows: the input module collects the superposition signal of the short wave signal and the noise signal and sends the superposition signal into the self-adaptive parameter estimation module. The self-adaptive parameter estimation module processes the input signal by utilizing a self-adaptive parameter estimation algorithm to obtain the steady state and dynamic parameters of the current system. The filter coefficient update module calculates and updates the coefficients of the adaptive filter based on the estimated steady state and dynamic parameters. The output module outputs the signal which is filtered by the adaptive filter for subsequent processing and application.
The adaptive parameter estimation algorithm mainly comprises two parts: the method comprises the steps of steady-state parameter estimation and dynamic parameter estimation.
The steady state parameter estimation is mainly used for estimating static parameters such as average power, signal to noise ratio and the like of signals, and the basic idea is to carry out sliding window processing on input signals, calculate the average power and the signal to noise ratio by using signal samples in a window, and determine initial coefficients of a suppression filter according to the parameters.
The dynamic parameter estimation is used for estimating the dynamic characteristics of the short wave signal, such as instantaneous frequency, phase, amplitude, etc., and the basic idea is to utilize mathematical tools such as autocorrelation function, cross correlation function, fast fourier transform, etc., to perform time domain and frequency domain analysis on the input signal, thereby obtaining the dynamic parameters of the signal. The dynamic parameter estimation algorithm has higher calculation complexity and implementation difficulty, but can reflect the dynamic characteristics of the short wave signals more accurately, so that the interference suppression effect is improved.
As shown in fig. 4, the flow of the adaptive parameter estimation algorithm is as follows:
step 1: and collecting an original short wave signal and a noise signal, and adding the original short wave signal and the noise signal to obtain a superposition signal.
Step 2: an adaptive recursive filter (IIR filter) is designed and an adaptive parameter estimation is implemented using LeakyLMS algorithm.
Step 3: initially, the weights of the filters are set to zero or random values.
Step 4: the superimposed signal is input to an adaptive recursive filter, resulting in a filtered signal.
Step 5: and the error signal is used as a feedback signal, and the parameters of the adaptive recursive filter are adjusted, so that the error signal is smaller and smaller, and short wave interference is further suppressed.
Step 6: and repeating the step 4 and the step 5 until the amplitude of the error signal reaches a certain threshold value or the filter converges to a certain steady-state value.
Step 7: and outputting the filtered signal, namely the signal after short wave interference is removed.
The core of the whole self-adaptive parameter estimation algorithm is to continuously update the weight by using the self-adaptive recursive filter, so that the performance of the self-adaptive recursive filter is continuously optimized, and finally, the effective suppression of short wave interference is achieved.
Claims (7)
1. A short wave interference suppression system based on self-adaptive parameters is characterized in that: the device comprises an input module, a self-adaptive filter and an output module which are electrically connected together in sequence, wherein the input module collects superposition signals of short wave signals and noise signals, the self-adaptive filter carries out filtering processing on the superposition signals, and the output module outputs the filtered signals.
2. The adaptive parameter-based short wave interference suppression system of claim 1, wherein: the input module adopts a short wave signal receiving circuit.
3. The short wave interference suppression system based on adaptive parameters of claim 2, wherein: the short wave signal receiving circuit adopts a superheterodyne receiving circuit or a direct conversion receiving circuit.
4. The adaptive parameter-based short wave interference suppression system of claim 1, wherein: the adaptive filter is a recursive filter.
5. The adaptive parameter-based short wave interference suppression system of claim 1, wherein: the adaptive filter is classified into a filter for suppressing differential mode interference and a filter for suppressing common mode interference.
6. The adaptive parameter-based short wave interference suppression system of claim 1, wherein: the self-adaptive filter comprises a self-adaptive parameter estimation module, a filter and a filter coefficient updating module, wherein the self-adaptive parameter estimation module is electrically connected with the input module and the filter respectively, the filter is electrically connected with the output module, and the filter coefficient updating module is electrically connected with the self-adaptive parameter estimation module and the filter respectively.
7. The adaptive parameter-based short wave interference suppression system of claim 6, wherein: the filters include a band-pass filter, a notch filter, and a high-pass filter.
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