A PSD-based adaptive frequency hopping method for suppressing adjacent channel interference in a PDT terminal device

Abstract

The present application relates to a kind of PDT terminal equipment processing methods based on PSD adaptive frequency hopping to suppress adjacent channel interference.The signal abnormal value filtering from radio frequency signal reception includes: radio frequency signal reception: through radio frequency module, the downlink / uplink signal of real-time acquisition PDT base station or terminal;Spectrum density analysis: the power spectrum density of received signal is calculated by fast Fourier transform, and the interference peak in spectrum is identified;Frequency hopping and threshold judgment: when it is judged that there is and interference continues to exceed preset frame number, adaptive frequency hopping is carried out according to the frequency band where interference is located, and the signal after frequency hopping is obtained;Down conversion, low-pass filtering and abnormal value filtering: the signal after frequency hopping is down converted, and Kaiser window filter and abnormal value filtering are used, and clean intermediate frequency signal is output for subsequent demodulation.The present application proposes the closed-loop solution of "spectrum sensing-dynamic threshold-adaptive frequency hopping-residual filtering", and realizes the accurate suppression of adjacent channel interference and the improvement of communication reliability.

Description

Technical Field

[0001] This invention belongs to the field of communications, specifically a PDT terminal device processing method based on PSD adaptive frequency hopping to suppress adjacent channel interference. Background Technology

[0002] As the core infrastructure of private network communication, the PDT system adopts a narrowband architecture based on the DMR (Digital Mobile Radio) standard, using 4FSK modulation at a channel spacing of 12.5kHz to achieve voice and low-speed data transmission. Although this design significantly improves spectrum utilization, it faces a serious ACI (Adaptive Channel Interference) problem.

[0003] The nonlinear characteristics of common PDT terminal radio frequency (RF) power amplifiers cause signal energy to spill over into adjacent channels. Alternatively, when the adjacent channel rejection of filters in commercial PDT terminals is low and strong signals exist in adjacent channels, interference signals can enter the target channel, degrading the downlink demodulation signal-to-interference-plus-noise ratio (SINR). In actual testing environments, when the difference between the target signal power and the adjacent channel interference power is greater than or equal to 60 dB, ACI (Average Interference Capacity) will disrupt the phase continuity of 4FSK and contaminate the correlation of the synchronization sequence, resulting in bit errors and time slot synchronization errors.

[0004] Traditional anti-ACI solutions primarily focus on the design of finite-length filters (FIRs) with high stopband suppression at the hardware level. While this method significantly improves adjacent channel selectivity (ACS), it increases terminal size and cost and cannot adapt to dynamic interference environments. Therefore, a new technology is needed to achieve ACI suppression in PDT terminals while maintaining a smaller printed circuit board (PCB) area. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the present invention aims to provide a PDT terminal device processing method based on PSD adaptive frequency hopping to suppress adjacent channel interference. The method is based on an adaptive frequency hopping scheme using power spectral density (PSD), and frequency hopping is achieved by modifying the configuration of the existing intermediate frequency chip, effectively solving the voice quality degradation problem caused by ACI.

[0006] The PDT terminal equipment processing method based on PSD adaptive frequency hopping to suppress adjacent channel interference is characterized by comprising the following steps:

[0007] S1. Radio frequency signal reception: The downlink / uplink signals of the PDT base station or terminal are captured in real time through the radio frequency module to obtain the received signal including adjacent channel interference;

[0008] S2. Spectral density analysis: Perform a fast Fourier transform on the received signal to calculate its power spectral density and identify interference peaks in the spectrum;

[0009] S3. Frequency Hopping and Threshold Judgment: Based on the analysis results of S2, combined with local noise power and historical adjacent channel interference statistics, a dynamic threshold is used to determine whether there is effective adjacent channel interference; when it is determined that there is interference and the interference continues to exceed the preset number of frames, adaptive frequency hopping is performed according to the frequency band where the interference is located to obtain the frequency-hopped signal;

[0010] S4. Down-conversion: The frequency-hopping signal is down-converted to obtain a zero intermediate frequency or low intermediate frequency signal;

[0011] S5. Low-pass filtering: The signal after down-conversion in S4 is subjected to out-of-band suppression and residual interference filtering using a preset filter to obtain a filtered signal;

[0012] S6. Outlier Filtering: Calculate the time-domain amplitude characteristics of the filtered signal, filter out abnormal sampling points that exceed the reasonable range, and output a clean intermediate frequency signal for subsequent demodulation.

[0013] According to the method of claim 1, the dynamic threshold determination in step S3 includes:

[0014] S301. Generate basic threshold ;

[0015] S302. Compare the power spectral density with the current threshold to determine if there is adjacent channel interference;

[0016] S303. When interference is detected, utilize the dynamic correction factor. The base threshold is updated to obtain the updated threshold. The dynamic correction factor It is generated at least based on the instantaneous rate of change of the power spectral density.

[0017] The method according to claim 2, characterized in that the dynamic correction factor The calculation formula is , A location factor related to the relative positions of the terminal and the base station. Weighting coefficients to suppress transient fluctuations.

[0018] According to the method of claim 1, the adaptive frequency hopping based on the frequency band of the interference in step S3 specifically includes:

[0019] S305. Calculate the root mean square power value of the received signal power spectral density in the frequency ranges [-7kHz, -5kHz] and [5kHz, 7kHz].

[0020] S306. Determine whether the interference is located on the left or right side of the target channel based on the root mean square power value; if the interference is located on the left, control the local oscillator to hop frequency 12.5kHz towards the high frequency direction; if the interference is located on the right, control the local oscillator to hop frequency 12.5kHz towards the low frequency direction.

[0021] According to the method described in claim 1, the preset filter in step S5 is a Kaiser window filter to complete the high-frequency suppression of the zero intermediate frequency signal in the down-conversion.

[0022] According to the method described in claim 1, the specific method for outlier filtering in step S6 is as follows: calculating the root mean square error of the amplitude of the filtered signal. ,in The signal length; This is the high-frequency suppression signal for the zero intermediate frequency signal after down-conversion, after traversal filtering. Each sampling point If satisfied or If the value of the sample point is zero, then the value of that sample point will be set to zero.

[0023] A PDT terminal device processing system for implementing the method of any one of claims 1-6, characterized in that it comprises:

[0024] The radio frequency receiving module is used to perform step S1;

[0025] A digital signal processor is used to execute steps S2, S3, S4, S5 and S6;

[0026] The digital signal processor is configured as follows:

[0027] The power spectral density is calculated and interference is identified using the spectrum analysis unit.

[0028] Through threshold judgment and frequency hopping control unit, interference is judged and frequency hopping control commands are generated based on dynamic threshold model;

[0029] The filtering and post-processing unit completes down-conversion, low-pass filtering, and outlier filtering operations.

[0030] The PDT terminal device is characterized in that it includes the system as described in claim 7.

[0031] A computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-6.

[0032] This invention innovatively utilizes PSD analysis to monitor adjacent channel interference intensity in real time. Without altering the 12.5kHz standard channel spacing of the PDT system or relying on protocol stack modifications, it dynamically selects the optimal operating frequency, solving problems such as high hardware modification costs and poor protocol compatibility in traditional solutions. Real-world test data shows that this solution can reduce the voice frame error rate (FER) under ACI in the DMR test standard from over 40% to below 8%. Attached Figure Description

[0033] Figure 1 This is a flowchart of an adaptive frequency hopping scheme based on PSD;

[0034] Figure 2 This is a PDT wireless channel model diagram;

[0035] Figure 3 This is the flowchart of the PSD adaptive threshold update module;

[0036] Figure 4 This is the design flowchart for the PSD adaptive threshold module;

[0037] Figure 5 This is a graph showing the power of adjacent channel interference signals versus the frame error rate. Detailed Implementation

[0038] With reference to the accompanying drawings, the technical solutions of each embodiment will be clearly and completely described below. It should be particularly noted that the embodiments described herein are only a partial representation of feasible implementations of the present invention, and not all possible implementations. Based on the embodiments disclosed in this document, any other implementations directly obtained or simply modified by those skilled in the art without creative effort should be considered to fall within the patent protection scope of the present invention.

[0039] This invention relates to a police digital trunking (PDT) wireless product, specifically addressing the issue of adjacent channel interference (ACI) signals entering the receiver outside the target channel, specifically at ±12.5 kHz, causing voice interruptions or data packet loss in low signal-to-noise ratio environments. This proposed solution is highly effective in suppressing ACI.

[0040] like Figure 1As shown in the figure, this paper discloses a PDT terminal device processing method based on PSD adaptive frequency hopping to suppress adjacent channel interference. The method mainly involves a frequency hopping algorithm for the received signal, including spectral density analysis, frequency hopping and threshold judgment, confirmation of the frequency range of the interference signal, down-conversion, high-frequency suppression, and outlier filtering. This process is effective in suppressing ACI and improving the voice quality of PDT.

[0041] (1) RF signal reception and spectral density analysis

[0042] First, it is necessary to analyze the base station transmission and channel models, such as the system model. Figure 2 As shown, this section forms the basis of the process below.

[0043] In digital trunking communication systems, the signals transmitted by the base station can be categorized into ACI signals and communication symbols used for downlink reception. Digital trunking base station systems are equipped with... A fixed sector antenna, it is for Each single-antenna digital trunking terminal provides communication services.

[0044] In the above system model, the PDT protocol uses quaternary frequency shift keying (4FSK) modulation with a bandwidth of 12.5kHz. A single terminal in the downlink... The received data can be represented as

[0045] (1)

[0046] In the formula and Represented as terminals The received data and the 4FSK modulation symbols transmitted by the base station, Defined as channel gain, and being perfectly known, its probability density function follows a Rayleigh distribution. This indicates that for users Co-channel interference and These are respectively represented as interference sources. To users Interference channel gain, Defined as a set of adjacent channel interference sources. This represents additive white Gaussian noise, whose mean and variance follow a set order. ,in addition Indicates user Receiver for interference sources The adjacent channel inhibition coefficient is expressed as follows:

[0047] (2)

[0048] In the formula Indicates user The frequency response of the receiving FIR filter, Represented as adjacent channel frequency offset (PDT) ),

[0049] During the frequency planning phase of the PDT system, co-channel interference has been effectively avoided through scientific frequency allocation. ,

[0050] single terminal Received data It can be simplified to

[0051] (3)

[0052] Therefore, the power of ACI can be expressed as formula (4).

[0053] (4)

[0054] In the formula Interference source Transmission power in the adjacent channel.

[0055] Combining formulas (3) and (4), the signal-to-interference-to-noise ratio (SINR) of this model can be obtained as follows:

[0056] (5)

[0057] in If the variance is additive white Gaussian noise, then the power spectral density curve of the received signal is...

[0058] (6)

[0059] in Representing the frequency index, combining equations (4) and (5), it can be seen that a method is needed to... By minimizing power, the SINR value of the terminal is increased, thereby reducing the bit error rate.

[0060] (2) Frequency hopping and threshold judgment

[0061] This section includes interference persistence verification and adaptive frequency hopping decision. The specific content of interference persistence verification is as follows: if the PSD exceeds the threshold and the number of persistences is ≥N, it is determined to be effective adjacent channel interference. The adaptive frequency hopping decision is to determine whether the interference is located within ±12.5kHz of the target channel (PDT standard channel spacing). If it is left-side interference, it will hop to a higher frequency band (+12.5kHz), and if it is right-side interference, it will hop to a lower frequency band (-12.5kHz) to avoid the interference overlapping with the target signal.

[0062] ACI is defined as interference signals appearing outside the target channel of the PDT (typically with a frequency offset of ±12.5kHz). Based on this characteristic, this scheme, upon detecting ACI on one side of the target channel, avoids strong interference bands through adaptive frequency hopping, and then further suppresses the residual ACI power to below the receiver noise floor using a low-pass FIR filter. Therefore, the implementation steps of this module are as follows:

[0063] Based on practical considerations, this proposal suggests an adaptive ACI detection threshold that combines the PSD power change rate (i.e., the historical average adjacent channel interference) with a dynamic correction factor. The specific process is as follows: Figure 3 As shown

[0064] First, the design of the basic threshold model, namely...

[0065] (7)

[0066] In the formula As the local noise power baseline, This represents the historical average of adjacent channel interference. The safety factor is used to reduce the probability of missed detections. A dynamic correction factor is added to this factor to reduce the probability of false alarms. The expression is:

[0067] (8)

[0068] in Defined as a location factor (related to whether the terminal is near a base station). Defined as a weighting factor to suppress transient fluctuations, This represents the rate of change of PSD power. This step utilizes... To identify sudden interference.

[0069] like Figure 4 As shown in the flowchart of the PDS frequency hopping implementation module, after completing the interference threshold judgment module, in view of the complex sudden interference in the wireless channel, this scheme designs a two-level protection mechanism to trigger frequency hopping only when the interference signal continuously covers more than N frames, so as to avoid misjudgment of instantaneous noise.

[0070] When the ACI is greater than N frames, the root mean square of the frequency range [-5kHz, -7kHz] and [5kHz, 7kHz] is calculated based on the power spectral density curve of the received signal. The range of the interference signal is determined using the result, and then low-IF frequency hopping is implemented.

[0071] (3) Down-conversion, low-pass filtering and outlier filtering

[0072] This section deals with the low-IF signal after frequency hopping. The signal undergoes down-conversion, utilizes a Kaiser window FIR filter, and outlier filtering to output a clean zero-IF signal. For subsequent demodulation. The model expression for this module is:

[0073] (9)

[0074] in , It is a low-to-medium frequency. This represents the signal time interval.

[0075] Design the coefficients of a low-pass FIR filter to suppress the high-frequency signal of the zero-IF signal after down-conversion. ,Right now

[0076] (10)

[0077] Finally, ACI suppression was achieved.

[0078] However, the high-frequency suppression signal of the zero intermediate frequency signal after downconversion Significant outliers (outliers) may still exist in the time domain. Therefore, an outlier filtering step is required. Specifically, the high-frequency suppression signal of the zero intermediate frequency signal after downconversion is calculated using formula (11). root mean square error ,in The signal length. If a certain sampling point... satisfy or If the value is zero, then the point is considered an outlier and is set to zero.

[0079] (11)

[0080] (4) Verification of communication metrics in real-world scenarios

[0081] This section completes the engineering implementation and uses charts to illustrate the performance advantages of the proposed solution.

[0082] This invention is achieved through the following technical solution, including the following steps:

[0083] S1. The purpose of this step, RF signal reception, is to capture the downlink signal of the PDT base station in real time and use this as the basis for calculating the signal power spectral density in the subsequent S2 step. Therefore, a single terminal receives a quaternary frequency shift keying (4FSK) modulated signal with ACI (adjacent channel interference). The expression is:

[0084]

[0085] In the formula and Represented as terminals The received data and the 4FSK modulation symbols transmitted by the base station, Defined as channel gain, and being perfectly known, its probability density function follows a Rayleigh distribution. This indicates that for users Co-channel interference and These are respectively represented as interference sources. To users Interference channel gain, Defined as a set of adjacent channel interference sources. This represents additive white Gaussian noise, whose mean and variance follow a set order. ,in addition Indicates user Receiver for interference sources The adjacent channel inhibition coefficient is expressed as follows:

[0086]

[0087] In the formula Indicates user The frequency response of the receiving FIR filter, Represented as adjacent channel frequency offset (PDT) ),

[0088] During the frequency planning phase of the PDT system, co-channel interference has been effectively avoided through scientific frequency allocation. ,

[0089] single terminal Received data It can be simplified to

[0090]

[0091] S2. This step is spectral density analysis. Based on step S1, the PSD is calculated to identify interference peaks in the spectrum and provide data support for subsequent dynamic threshold determination.

[0092] First, complete the derivation of the initial signal SINR, that is...

[0093]

[0094] in Since the variance is additive white Gaussian noise, the ACI power formula is:

[0095]

[0096] In the formula Interference source The transmit power in the adjacent channel; subsequently, based on this, the power spectral density curve of the received signal is derived, namely:

[0097]

[0098] S3. Frequency hopping and threshold determination: Combine local noise power measurement (collected through silent time slots) and historical adjacent channel interference averages to generate real-time interference thresholds through dynamic correction factors;

[0099] S3 includes the following sub-steps:

[0100] S301. This section comprises two steps: generating local noise power measurements and generating historical adjacent channel interference measurements. A threshold is ultimately generated based on the outputs of these two steps. This step (S301) updates the dynamic correction factor calculated in S303. The updated threshold is then fed back to the interference threshold judgment of S302;

[0101] First, using the SINR obtained in S2 and Complete the initial threshold threshold Generation, that is:

[0102]

[0103] In the formula As the local noise power baseline, The historical average interference between adjacent channels is set separately. This is a safety margin used to reduce the probability of missed detections;

[0104] If interference is detected in S302, then the threshold needs to be updated based on the dynamic correction factor in S303.

[0105]

[0106] in Defined as a dynamic correction factor;

[0107] S302. This is for determining the interference threshold, which is based on the current threshold generated in S301. or the updated threshold The value is compared with the current power spectral density value calculated by S2; if an ACI is found, the frequency hopping process is initiated; if no ACI is found, the normal processing process is initiated directly.

[0108] S303. This section generates a dynamic correction factor for the presence of interfering signals. Its purpose is to reduce the false alarm probability expression is as follows:

[0109]

[0110] in Defined as a location factor, this parameter is related to whether it is near a base station. Defined as a weighting factor to suppress transient fluctuations, The PSD power change rate; this step is used to identify sudden interference and implement threshold update feedback to S301;

[0111] S304. If ACI is detected in S302, the anti-false triggering mechanism is activated. If the interference continues for more than [time period missing], the mechanism will be activated. The subsequent ACI frequency hopping selection mechanism is only triggered when a frame is in use;

[0112] S305. If the condition in S304 is met, the process proceeds to determine the frequency of the ACI. The purpose of this process is to select the optimal frequency hopping position of the signal in order to suppress ACI interference.

[0113] Based primarily on the power spectral density (PSD) curve of the received signal, the root mean square (RMS) power values ​​within the frequency ranges [-7kHz, -5kHz] and [5kHz, 7kHz] are calculated to determine the specific frequency band (left or right) where the interfering signal is located.

[0114] S306. Based on the ACI position determined in S305, complete the low-IF signal after frequency hopping. Frequency hopping is divided into positive bias and negative bias, that is:

[0115]

[0116] in , It is a low-to-medium frequency. This represents the signal time interval.

[0117] S4. This part is the down-conversion module. Low-IF signals cannot be processed directly, so down-conversion is required; it mainly relies on the low-IF signal obtained from S3. After down-conversion, it becomes a zero intermediate frequency signal. ,Right now

[0118]

[0119] S5. Using a Kaiser window FIR filter, out-of-band interference is suppressed to achieve zero-IF signal. High-frequency suppression, i.e.

[0120]

[0121] in This is the high-frequency suppression signal for the zero intermediate frequency signal after down-conversion. This refers to the frequency domain response of a high-frequency suppression FIR filter.

[0122] S6. Outlier filtering: The signal after passing through the FIR filter. There may be significant time-domain waveform protrusions, therefore outlier filtering is necessary. This is achieved by calculating the root mean square error of the signal, i.e.,

[0123]

[0124] in Given the signal length, if or Then determine .

[0125] This innovative solution utilizes PSD analysis to monitor adjacent channel interference intensity in real time. Without altering the 12.5kHz standard channel spacing of the PDT system or relying on protocol stack modifications, it dynamically selects the optimal operating frequency, perfectly solving the problems of high hardware modification costs and poor protocol compatibility in traditional solutions. Real-world test data shows that this solution can reduce the voice frame error rate (FER) under ACI in the DMR test standard from over 40% to below 8%.

[0126] Without loss of generality, the receiver low-pass FIR filter Set to the internal parameters of the intermediate frequency chip. The location factor is set to 0.8, indicating that under conditions near the base station, This is achieved by using a table lookup method, reducing the computational complexity of the algorithm and the weighting coefficients. It was set to 0.2.

[0127] Figure 5 The frame error rate (FER) of this scheme and the traditional scheme as a function of the interference signal power were plotted when ACI interference was present at ±12.5kHz in the target channel. The main channel signal power was fixed at -117dBm during the test. As can be observed from the figure, under the same interference power, the frame error rate of this scheme is significantly lower than that of the traditional scheme, equivalent to a gain of approximately 5-6 dB in adjacent channel selectivity (ACS). As shown in Table 1, the measured ACS values ​​of this scheme at the ±12.5kHz interference frequency offset reached 66 dB and 65 dB, respectively, while the traditional scheme only achieved 59 dB and 58 dB.

[0128] Compared with the DMR standard, this scheme significantly improves the ACI suppression performance in all interference frequency bands. The measured results are shown in Table 1 below.

[0129] Table 1 Adjacent Channel Selectivity Table

[0130] Interference frequency band (kHz) DMR standard (dB) Measured values ​​in this scheme -12.5 60 66 +12.5 60 65 -25 65 74 +25 65 74 -50 70 78 +50 70 78 -100 75 85 +100 75 85

[0131] This invention applies to solutions integrating RF and intermediate frequency (IF) signals, and such solutions must be able to support IF configuration. Figure 1 The mid-to-low frequency receiving section is mainly configured through RF chips. Its offset frequency is related to the 4FSK demodulation sampling rate, as well as the received signal bandwidth and modulation frequency offset in the PDT protocol.

[0132] Spectral density analysis, frequency hopping, and threshold determination all need to be implemented in a digital signal processor (DSP). The flow of the frequency domain energy threshold determination module is as follows: Figure 3 This depends on historical values ​​from ACI, requires continuous iteration, and some parameters need to be configured according to the actual scenario.

[0133] The downconverter module needs to generate a corresponding mixing signal based on the low-IF frequency deviation, and then implement the mixing algorithm through the above expression 8 to mix and filter the low-IF signal into a zero-IF signal.

[0134] In summary, by real-time monitoring of the signal PSD distribution, the location of adjacent channel interference frequency points can be identified; when the interference continues to exceed a preset threshold, the local oscillator frequency is dynamically adjusted to achieve channel switching and avoid strong interference frequency points; then, a preset low-pass FIR filter is used to suppress residual out-of-band interference (including residual ACI) in the signal after frequency hopping; the method is implemented by improving the digital signal processing flow of the intermediate frequency chip, and has the advantages of being compatible with existing hardware, having a fast response speed, and a low false trigger rate.

[0135] English abbreviations Full English name Full Chinese name ACI Adjacent Channel Interference Adjacent channel interference ACS Adjacent Channel Selectivity Adjacent channel selectivity DSP Digital Signal Processor Digital Signal Processor FIR Finite Impulse Response Finite long impulse response PCB Printed Circuit Board Printed Circuit Board PSD Power Spectral Density Power spectral density RF Radio Frequency Radio frequency ULA Uniform linear array Uniform linear array SINR Signal to Interference plus Noise Ratio Signal-to-interference-to-noise ratio

Claims

1. A PDT terminal equipment processing method based on PSD adaptive frequency hopping to suppress adjacent channel interference, characterized in that, Includes the following steps: S1. Radio frequency signal reception: The downlink / uplink signals of the PDT base station or terminal are captured in real time through the radio frequency module to obtain the received signal including adjacent channel interference; S2. Spectral density analysis: Perform a fast Fourier transform on the received signal to calculate its power spectral density and identify interference peaks in the spectrum; S3. Frequency Hopping and Threshold Judgment: Based on the analysis results of S2, combined with local noise power and historical adjacent channel interference statistics, a dynamic threshold is used to determine whether there is effective adjacent channel interference; when it is determined that there is interference and the interference continues to exceed the preset number of frames, adaptive frequency hopping is performed according to the frequency band where the interference is located to obtain the frequency-hopped signal; S4. Down-conversion: The frequency-hopping signal is down-converted to obtain a zero intermediate frequency or low intermediate frequency signal; S5. Low-pass filtering: The signal after down-conversion in S4 is subjected to out-of-band suppression and residual interference filtering using a preset filter to obtain a filtered signal; S6. Outlier Filtering: Calculate the time-domain amplitude characteristics of the filtered signal, filter out abnormal sampling points that exceed the reasonable range, and output a clean intermediate frequency signal for subsequent demodulation.

2. The method according to claim 1, characterized in that, The dynamic threshold determination in step S3 includes: S301. Generate basic threshold ; S302. Compare the power spectral density with the current threshold to determine if there is adjacent channel interference; S303. When interference is detected, utilize the dynamic correction factor. The base threshold is updated to obtain the updated threshold. The dynamic correction factor It is generated at least based on the instantaneous rate of change of the power spectral density.

3. The method according to claim 2, characterized in that, The dynamic correction factor The calculation formula is , A location factor related to the relative positions of the terminal and the base station. Weighting coefficients to suppress transient fluctuations.

4. The method according to claim 1, characterized in that, The adaptive frequency hopping based on the frequency band of the interference described in step S3 specifically includes: S305. Calculate the root mean square power value of the received signal power spectral density in the frequency ranges [-7kHz, -5kHz] and [5kHz, 7kHz]. S306. Determine whether the interference is located on the left or right side of the target channel based on the root mean square power value; if the interference is located on the left, control the local oscillator to hop frequency 12.5kHz towards the high frequency direction; if the interference is located on the right, control the local oscillator to hop frequency 12.5kHz towards the low frequency direction.

5. The method according to claim 1, characterized in that, The preset filter mentioned in step S5 is a Kaiser window filter, which completes the high-frequency suppression of the zero intermediate frequency signal in the down-conversion.

6. The method according to claim 1, characterized in that, The specific method for outlier filtering in step S6 is as follows: calculate the root mean square error of the amplitude of the filtered signal. ,in The signal length; This is the high-frequency suppression signal for the zero intermediate frequency signal after down-conversion, after traversal filtering. Each sampling point If satisfied or If the value of the sample point is zero, then the value of that sample point will be set to zero.

7. A PDT terminal device processing system for implementing the method according to any one of claims 1-6, characterized in that, include: The radio frequency receiving module is used to perform step S1; A digital signal processor is used to execute steps S2, S3, S4, S5 and S6; The digital signal processor is configured as follows: The power spectral density is calculated and interference is identified using the spectrum analysis unit. Through threshold judgment and frequency hopping control unit, interference is judged and frequency hopping control commands are generated based on dynamic threshold model; The filtering and post-processing unit completes down-conversion, low-pass filtering, and outlier filtering operations.

8. A PDT terminal device, characterized in that, It includes the system as described in claim 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-6.

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