A processing method of a PDT terminal device based on dynamic intermediate frequency selection and radio software anti-jamming

Abstract

The present application relates to a kind of radio software anti-blocking interference based on dynamic intermediate frequency selection PDT terminal equipment processing method.It is characterized in that the following steps are included:S1:radio frequency signal reception;S2:blocking interference detection and decision;S3:intermediate frequency configuration selection;S4:radio frequency signal processing;S5:high frequency suppression.The present application is by real-time detection blocking interference in channel, adaptively switches between "zero intermediate frequency" and "low intermediate frequency" two receiving modes;When there is no interference or weak interference, it uses the simple structure of zero intermediate frequency mode to reduce power consumption and complexity;When detecting strong blocking interference, it is automatically switched to low intermediate frequency mode, and the interference is moved to the high frequency area that can be filtered out by spectrum shift, so as to guarantee signal quality.

Description

Technical Field

[0001] This invention belongs to the field of communications, and specifically relates to a PDT terminal device processing method based on dynamic intermediate frequency selection for radio software anti-blocking interference. Background Technology

[0002] Currently, PDT, as a high-efficiency digital trunking communication system designed specifically for professional users (such as emergency response and transportation), allows terminal devices in digital trunking communication systems to perform multiple functions such as voice communication, SMS, and data transmission, meeting the communication needs of different industries and scenarios. Simultaneously, trunking terminals also have location sharing and positioning functions, enabling terminal tracking and scheduling. Compared to traditional analog trunking and some other digital trunking technologies, it is even more necessary to avoid the blocking interference (BI) problem of traditional analog systems and reduce the impact of receiver saturation caused by strong signals.

[0003] Most domestic PDT-related products use a hardware architecture that separates intermediate frequency (IF) and radio frequency (RF) processing. While this design offers excellent performance in blocking interference suppression, it involves more peripheral circuitry, higher power consumption, and higher cost compared to integrated IF and RF solutions. Integrated PDT wireless products, on the other hand, have a smaller printed circuit board (PCB) area, which can be reduced by 30% to 50% compared to traditional solutions. They also have a wider range of applications.

[0004] While integrated intermediate frequency (IF) and radio frequency (RF) solutions offer a balance between low power consumption and high performance, they suffer from significant challenges in suppressing jamming interference. Therefore, a low-IF-based solution is needed. 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 dynamic intermediate frequency selection for radio software anti-blocking interference.

[0006] The aforementioned method for processing PDT terminal equipment based on dynamic intermediate frequency selection for radio software anti-jamming interference is characterized by comprising the following steps: S1. Radio Frequency Signal Reception: Establish the received signal model of the PDT downlink, receive radio frequency signals and obtain discrete signal sequences; S2. Blocking Interference Detection and Decision: Based on the discrete signal sequence, frequency domain analysis is performed to calculate the energy statistical characteristics of a specific frequency band, and the results are compared with a preset decision threshold to determine whether there is blocking interference in the current channel, and a binary decision result is output. S3. Intermediate Frequency (IF) Configuration Selection: Dynamically configure the IF mode of the receiver based on the binary decision result; if the decision indicates no jamming interference, configure the receiver in zero IF mode; if the decision indicates jamming interference, configure the receiver in low IF mode. S4. Radio Frequency Signal Processing: Processing the selected intermediate frequency received signal: When the receiver is configured in low intermediate frequency mode, the low intermediate frequency received signal is down-converted to shift the useful signal to the baseband, while shifting the blocking interference to a higher frequency. S5. High-frequency suppression: The signal is filtered according to the current intermediate frequency mode; for zero intermediate frequency mode, a baseband low-pass filter is used; for low intermediate frequency mode, a low-pass filter is used to filter out the blocking interference located at the high frequency after down-conversion, so as to obtain the purified baseband signal.

[0007] The method is characterized in that, in step S2, determining whether there is blocking interference in the current channel specifically includes: S201. Calculate the power spectral density estimate of the discrete signal sequence; S202. Based on the Neyman-Pearson criterion, calculate the decision threshold according to the preset false alarm probability; S203. Calculate the ratio of energy in the target frequency band to energy in the entire frequency band as a detection statistic, and compare the statistic with the decision threshold to determine whether there is blocking interference.

[0008] The method is characterized in that, in step S202, the decision threshold... Calculated using the following formula: ,in For the generalized Marcum Q function and These represent the expected value and variance under the null hypothesis, respectively. This represents the probability of a false alarm. It is the inverse function of the generalized Marcum Q function.

[0009] The method is characterized in that, in step S4, the downconversion process is achieved by multiplying the low intermediate frequency received signal with a complex conjugate low intermediate frequency local oscillator signal.

[0010] The method is characterized in that, in step S3, the intermediate frequency in the low-intermediate frequency mode is... It is configured to be half the bandwidth of the PDT signal.

[0011] The method is characterized in that, in step S5, the low-pass filter used for the low-intermediate frequency mode is a finite-length impulse response filter.

[0012] The method is characterized in that the finite impulse response filter is designed using a Kaiser window.

[0013] The aforementioned PDT terminal device for resisting jamming interference based on dynamic intermediate frequency selection is characterized by comprising: a radio frequency receiving module for receiving radio frequency signals and acquiring discrete signal sequences; an interference detection and decision module for performing frequency domain analysis based on the discrete signal sequences, calculating the energy statistical characteristics of a specific frequency band, comparing them with a preset decision threshold, determining whether jamming interference exists in the current channel, and outputting a binary decision result; an intermediate frequency configuration control module for dynamically configuring the intermediate frequency mode of the receiver according to the binary decision result; if the decision indicates no jamming interference, configuring the receiver to zero intermediate frequency mode; if the decision indicates the presence of jamming interference, configuring the receiver to low intermediate frequency mode; a signal processing module for down-converting the low intermediate frequency received signal when the receiver is configured to low intermediate frequency mode, shifting the useful signal to the baseband, and simultaneously shifting the jamming interference to a higher frequency; and a filtering module for filtering the signal according to the current intermediate frequency mode; for zero intermediate frequency mode, using a baseband low-pass filter; for low intermediate frequency mode, using a low-pass filter to filter out the jamming interference located at a higher frequency after down-conversion, obtaining a purified baseband signal.

[0014] The device is characterized in that the interference detection and decision module is specifically used for: calculating the power spectral density estimate of the discrete signal sequence; calculating the decision threshold based on the Neyman-Pearson criterion and a preset false alarm probability; calculating the ratio of the target frequency band energy to the full frequency band energy as a detection statistic, and comparing it with the decision threshold to make a decision.

[0015] The device is characterized in that the signal processing module achieves down-conversion by multiplying the low-IF received signal with a complex conjugate low-IF local oscillator signal.

[0016] This invention adaptively switches between two receiving modes, "zero intermediate frequency" and "low intermediate frequency," by detecting blocking interference in the channel in real time. When there is no interference or weak interference, the simple zero intermediate frequency mode is used to reduce power consumption and complexity. When strong blocking interference is detected, it automatically switches to the low intermediate frequency mode and moves the interference to a filterable high-frequency region through spectrum shifting, thereby ensuring signal quality.

[0017] This invention can mix a received radio frequency signal (i.e., the in-phase component (I) and the quadrature component (Q)) to a predetermined low-IF frequency range. This scheme improves reliability while ensuring effectiveness, effectively avoids the zero-frequency impulse response caused by strong signals (i.e., direct current (DC) interference), and enhances the system's anti-BI performance.

[0018] This invention is a digital trunking (PDT) wireless product. It is particularly effective in suppressing blocking interference when strong signals enter the receiver, causing overload or saturation of the receiver's front-end circuitry. Attached Figure Description

[0019] Figure 1 The flowchart shows the blocking suppression PDT scheme based on dynamic intermediate frequency selection.

[0020] Figure 2 A diagram of a digital trunking communication model;

[0021] Figure 3 Here is a flowchart for the blocking interference detection process;

[0022] Figure 4 This is a flowchart of radio frequency signal reception and processing.

[0023] Figure 5 Spectrum diagrams for zero intermediate frequency and low intermediate frequency;

[0024] Figure 6 The spectrum diagrams are for low-mid frequency and down-conversion frequencies.

[0025] Figure 7 This is the filtered spectrum. Detailed Implementation

[0026] 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 some examples 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.

[0027] With the rapid popularization of wireless communication technology, jamming interference has become a key bottleneck restricting receiver performance. Traditional zero-IF receivers are simple in structure and low in power consumption, but are susceptible to DC offset and low-order interference, leading to a deterioration in signal-to-interference-plus-noise ratio (SINR). Low-IF receivers, by down-converting the signal to a non-zero IF, can effectively avoid jamming interference, but this increases the complexity of frequency conversion and hardware overhead. To resolve this contradiction, this paper proposes an adaptive IF receiver scheme based on real-time interference detection, which realizes dynamic switching between zero-IF and low-IF configurations, balancing system complexity and anti-interference performance.

[0028] The basic process of this plan is as follows: Figure 1 As shown, this section introduces the implementation of the DPT anti-blocking interference scheme under the integrated framework, including channel environment analysis, technical solution implementation, and further explanation of its technical effects through simulation.

[0029] (1) Radio frequency signal reception and wireless channel model analysis

[0030] This approach begins with the analysis of the downlink received signal in a digital trunking communication system (PDT). In such systems, the signals transmitted by the base station can be categorized as high-power interference signals and communication symbols used for downlink reception. For example... Figure 2 As shown, in a digital trunking base station system equipped with The antenna is a Uniform Linear Array (ULA) structure, which provides... Each single-antenna digital trunking terminal provides communication services.

[0031] 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

[0032] (1)

[0033] In the formula Indicates length is Offline signal sequences, and Representing users respectively The channel gain and the 4FSK modulated signal transmitted by the base station; terminal Simultaneous slot interference is defined as ,in Defined as a signal to the user The interference coefficient, and These represent the channel gain and the blocking interference signal, respectively. This represents additive white Gaussian noise, whose mean and variance follow a set order. Furthermore, assuming the user Channel gain The probability density function of the given channel is perfectly known and follows a Rayleigh distribution. Specifically, this is based on a time-division multiple access channel model with good time slot isolation. Therefore, the channel model can be simplified to:

[0034] (2)

[0035] The power of the blocking interference signal can be expressed as:

[0036] (3)

[0037] In the formula This is expressed as instantaneous blocking interference power; the receiver sensitivity of a PDT is typically...

[0038] (4)

[0039] Therefore, the blocking signal power Exceeding the receiver's dynamic range, i.e. , This refers to the dynamic range, which leads to a decrease in receiver reliability. In practical PDT applications, blocking signals raise the noise floor, causing SINR degradation; therefore, identifying and suppressing blocking signals is crucial. This is key to improving reception performance.

[0040] (2) Blocking interference detection

[0041] like Figure 3 As shown, interference detection is performed in real time in a digital signal processor (DSP). The process is as follows: calculate the power spectrum of the received signal, extract feature values, compare them with a preset threshold, and finally output a binary decision result.

[0042] The power spectral density statistics are calculated, i.e.

[0043] (5)

[0044] in Defined as received signal Discrete power spectrum estimation, This is the set of indices for the discrete Fourier transforms of the frequency band to be detected. Therefore, the range of the target frequency band for jamming interference is defined as...

[0045] (6)

[0046] in This indicates the spectral location of the blocking interference. Sampling frequency, Since the center frequency is given, the relative energy ratio is expressed as...

[0047] (7)

[0048] According to the Neyman-Pearson criterion, the optimal detection performance is achieved when the false alarm probability does not exceed a pre-set limit. Based on the relative energy ratio detection of S201, the maximum likelihood ratio estimate can be obtained.

[0049] (8)

[0050] in and These represent binary hypothetical models with and without blocking interference, respectively. Therefore, based on... The rules for obtaining the judgment are as follows Therefore, the false alarm probability is fixed according to the Neyman-Pearson criterion. The threshold can be obtained. The expression is

[0051] (9)

[0052] in For the generalized Marcum Q function and These represent the expectation and variance under the null hypothesis, respectively.

[0053] At this point, the detection module has completed the logical state output from signal to "interference present / absent," which will be directly used to control subsequent hardware configuration.

[0054] (3) Low IF / zero IF receiver configuration

[0055] This step serves as a bridge connecting detection and processing; based on the decision result output from step 2, the RF chip and digital processing link are configured via control signals:

[0056] The result was no interference: the local oscillator was configured so that the receiver operated in zero-IF mode.

[0057] The result indicates interference: Configure the local oscillator to operate the receiver in low-IF mode, with the IF frequency... It is usually set to half of the signal bandwidth.

[0058] (4) Signal processing in low-to-medium frequency mode

[0059] This step only considers the low-to-mid frequency configuration. The specific process is as follows: Figure 4 As shown.

[0060] Therefore, the implementation of the low-IF signal mainly depends on the configuration of the integrated chip used by the PDT (implementation depends on configuration), which mixes the RF received signal to the IF signal. According to the PDT protocol, half of the PDT signal bandwidth is the low-IF frequency offset, so the low-IF received signal is...

[0061] (10)

[0062] in It is a low-to-intermediate frequency signal, that is

[0063] (11)

[0064] in It is a low-to-medium frequency. This represents the time interval of the signal.

[0065] Based on equation (10). Figure 5 Spectrum diagrams of the zero-IF and low-IF signals were plotted. The 4FSK modulation frequency offsets according to the PDT protocol are (648Hz, -648Hz, -1944Hz, 1944Hz). A significant DC current (DC) is observed at zero frequency. Therefore, for integrated PDT terminals, the presence of DC causes distortion in the zero-IF signal. The four frequency components of the low-IF 4FSK are clearly visible, effectively avoiding the SINR degradation caused by DC.

[0066] Low- and intermediate-frequency signals cannot be directly demodulated in normal baseband processing. Therefore, they are shifted to zero frequency for further IQ data processing, resulting in a down-converted signal. The expression is

[0067] (12)

[0068] Based on equation (12), the spectrum after downconversion is as follows: Figure 6 As shown. The key effect is that the useful signal is moved back to baseband (near zero frequency), while blocking interference and residual DC components are shifted to a frequency range of [missing information]. This is centered on the high-frequency region. This lays a decisive foundation for the next step of separating the signal from the interference using a low-pass filter.

[0069] (5) High frequency suppression

[0070] This is the core step in eliminating interference.

[0071] Low-pass filtering can effectively remove blocking interference after mixing; its expression is:

[0072] (13)

[0073] In the formula for A Kaiser window finite impulse response (FIR) filter, i.e. ,in Defined as Kaiser window function [5] , can be represented as

[0074] -1 (14)

[0075] In equation (14) For zero-order modified Bessel functions, For shape parameters, .

[0076] The final signal spectrum after filtering by combining equations (13) and (14) is as follows Figure 7 As shown, high-frequency blocking interference and DC components have been effectively suppressed, while the useful signal in the baseband is preserved with a clear outline. This signal can then be sent to the demodulator for further processing, thereby significantly improving its anti-blocking interference capability without sacrificing the advantages of the integrated receiver's size and power consumption.

[0077] The present invention also provides a PDT terminal device based on dynamic intermediate frequency selection to resist jamming interference, comprising:

[0078] The radio frequency (RF) receiver module is used to receive RF signals and acquire discrete signal sequences.

[0079] The interference detection and decision module is used to perform frequency domain analysis based on the discrete signal sequence, calculate the energy statistical characteristics of a specific frequency band, compare them with a preset decision threshold, determine whether there is blocking interference in the current channel, and output a binary decision result.

[0080] The intermediate frequency (IF) configuration control module is used to dynamically configure the IF mode of the receiver according to the binary decision result; if the decision is that there is no blocking interference, the receiver is configured to zero IF mode; if the decision is that there is blocking interference, the receiver is configured to low IF mode.

[0081] The signal processing module is used to downconvert the low-IF received signal when the receiver is configured in low-IF mode, shifting the useful signal to the baseband and shifting the blocking interference to a higher frequency.

[0082] The filtering module is used to filter the signal according to the current intermediate frequency mode. For the zero intermediate frequency mode, a baseband low-pass filter is used; for the low intermediate frequency mode, a low-pass filter is used to filter out the blocking interference located at the high frequency after down-conversion, so as to obtain the purified baseband signal.

[0083] Specifically, the interference detection and decision module is used to: calculate the power spectral density estimate of the discrete signal sequence; calculate the decision threshold based on the Neyman-Pearson criterion and the preset false alarm probability; calculate the ratio of the target frequency band energy to the total frequency band energy as a detection statistic, and compare it with the decision threshold to make a decision.

[0084] The signal processing module achieves down-conversion by multiplying the low-IF received signal with a complex conjugate low-IF local oscillator signal.

[0085] This invention is implemented through the following steps:

[0086] S1. Radio frequency signal reception

[0087] This step aims to establish a received signal model for the PDT downlink, providing a theoretical basis for subsequent interference detection. Considering a system with multiple users, the received signal of a single terminal k can be modeled as a superposition of useful signal, blocking interference, and noise:

[0088]

[0089] In the formula Indicates length is Offline signal sequences, and Representing users respectively The channel gain and the 4FSK modulated signal transmitted by the base station. Terminal Simultaneous slot interference is defined as ,in Defined as a signal to the user The interference coefficient, and These are represented as the channel gain of the jamming signal and the jamming signal, respectively. This represents additive white Gaussian noise, whose mean and variance follow a set order. Furthermore, assuming the user Channel gain It is perfectly known and its probability density function follows a Rayleigh distribution.

[0090] Furthermore, assuming the user Channel gain The probability density function of the given channel is perfectly known and follows a Rayleigh distribution. Specifically, this is based on a time-division multiple access channel model with good time slot isolation. Therefore, the channel model can be simplified to...

[0091]

[0092] S2. Blocking Interference Detection and Decision

[0093] The purpose of this step is to identify in real time whether there is strong blocking interference in the current channel that needs to be addressed. The result is a key basis for triggering intermediate frequency mode switching. The detection process is as follows:

[0094] S201. Calculate the power spectral density statistics: First, for the discrete signal sequence received in step S1... Perform frequency domain analysis to calculate its power spectral density estimate. In order to observe the distribution of signal energy in the frequency domain.

[0095]

[0096] in Defined as received signal Discrete power spectrum estimation, This is the set of indices for the discrete Fourier transform corresponding to the frequency band to be detected. Therefore, the range of the target frequency band for jamming interference is... Defined as

[0097]

[0098] in This indicates the spectral location of the blocking interference. Sampling frequency, The center frequency. Therefore, the relative energy ratio Represented as

[0099]

[0100] S202. Neyman-Pearson Criterion Threshold Setting: Defined at the center frequency of potential interference. The core of the frequency band to be detected Calculate the ratio of energy within the frequency band to energy outside the band. As a detection statistic, it is used to determine the probability of a false alarm given a false alarm probability. To achieve optimal detection performance, the decision threshold is set using the Neyman-Pearson criterion. Based on the relative energy ratio detection of S201, the maximum likelihood ratio estimate can be obtained.

[0101]

[0102] in and These represent binary hypothetical models with and without blocking interference, respectively. Therefore, based on... The rules for obtaining the judgment are as follows Therefore, the false alarm probability is fixed according to the Neyman-Pearson criterion. The threshold can be obtained. The expression is

[0103]

[0104] in For the generalized Marcum Q function and These represent the expected value and variance under the null hypothesis, respectively.

[0105] S203. Blocking Interference Judgment: Comparison Statistics With threshold :like The judgment is then "there is blocking interference" (assuming...). Otherwise, the judgment is "non-blocking interference" (assuming...). The decision result ("with or without interference") will be directly output to step S3 to control the operating mode of the receiver.

[0106] S3. Low IF / Zero IF Receiver Configuration

[0107] This step, based on the decision result of S2, dynamically configures the receiver's hardware or digital processing link.

[0108] If the judgment is "no blocking interference", the receiver will be configured to zero intermediate frequency (Zero-IF) mode. In this mode, the signal is directly down-converted to baseband, with the shortest processing link and the lowest power consumption.

[0109] If the determination is "interference exists", the receiver will be configured to Low-IF mode; in this mode, the signal will be down-converted to a non-zero low-IF. This creates conditions for subsequent interference filtering.

[0110] S4. Radio Frequency Signal Reception and Processing

[0111] This step is performed only when the system is configured in low-IF mode; its purpose is to move useful signals and interference that are already at low-IF frequency back to baseband through secondary downconversion, while moving blocking interference to higher frequencies.

[0112] S401. Low-IF RF signal reception: This is completed at the RF front-end. If the RF receiver is configured for zero IF, it jumps directly to S5; otherwise, it enters the low-IF reception process. The low-IF signal received by a single terminal can be represented as follows:

[0113]

[0114] in It is a low-to-intermediate frequency signal, that is

[0115]

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

[0117] S402. Down-conversion: Low-IF signals cannot be directly demodulated in normal baseband processing, so they need to be shifted to zero frequency before the IQ data is processed. The expression is as follows:

[0118]

[0119] S5. High-frequency suppression

[0120] This step is the final stage in eliminating interference, and appropriate filtering strategies are adopted according to different intermediate frequency modes.

[0121] For zero-IF mode: Since the signal is already in the baseband, a baseband low-pass filter with bandwidth matching the signal is used directly to filter out out-of-band noise and possible weak in-band interference.

[0122] For low-to-intermediate frequency (LIFM) mode: The signal has been processed by S402, and the blocking interference is located at high frequency. By using a reasonably designed anti-aliasing / reconstruction low-pass filter with a cutoff frequency, the blocking interference components located at high frequency can be effectively filtered out, while the useful signal located in the baseband can be completely preserved.

[0123]

[0124] Filtered signal This is the purified baseband signal, which can be directly used for subsequent demodulation and other processing, thus solving the problem of SINR degradation caused by blocking interference.

[0125] The core design of this invention comprises three key modules: First, after acquiring the signal via radio frequency reception, frequency domain features are extracted by calculating the power spectral density statistics, and then a threshold is set using the Neyman-Pearson criterion to accurately determine whether blocking interference exists. Second, the intermediate frequency (IF) configuration is adaptively selected based on the interference detection results: zero IF is selected when there is no interference to maintain low system complexity; when interference exists, it switches to low IF and down-converts the interference signal to a higher frequency band. Finally, high-frequency suppression is applied to the low IF signal, or high-frequency filtering is applied directly to the zero IF signal to completely eliminate residual interference. This scheme achieves dynamic adjustment of the IF configuration through real-time interference detection, combining the simplicity of zero IF with the high anti-interference capability of low IF. Experimental results show that compared with a fixed IF configuration, the system improves the SINR by 5-8 dB under blocking interference conditions, significantly improving reception reliability and making it suitable for wireless communication systems in complex interference environments.

[0126] This invention applies to solutions that integrate radio frequency and intermediate frequency, and the solution must be able to support intermediate frequency 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.

[0127] The downconversion module is mainly implemented in the digital signal processor (DSP). It needs to generate a corresponding mixing signal based on the low-IF frequency offset, and then implement the mixing algorithm through the above expression (12) to mix and filter the low-IF signal into a zero-IF signal. The result is as follows: Figure 6 As shown.

[0128] The high-frequency suppression module is also implemented at the DSP. First, it needs to be designed according to Equation (14) to meet the physical layer design requirements specified in the PDT protocol, that is, to ensure the sensitivity of the PDT terminal device while improving the stopband suppression effect.

[0129] In summary, to overcome the problem of front-end circuit saturation caused by the inability of integrated solutions to effectively suppress strong signals, this solution provides a PDT terminal equipment processing method based on dynamic intermediate frequency (IF) selection for radio software to resist jamming interference. This solution not only avoids the degradation of the signal-to-interference-plus-noise ratio (SINR) caused by the zero IF response of high power spectral density on useful signals, but also shifts and filters out jamming interference by combining spectrum shifting and high-frequency suppression, thereby ensuring signal integrity.

[0130] English abbreviations Full English name Full Chinese name BI Blocking Interference Blocking interference DC Direct Current DC DSP Digital Signal Processor Digital Signal Processor FIR Finite Impulse Response Finite long impulse response I In-Phase In-phase component Q Quadrature Orthogonal components PCB Printed Circuit Board Printed Circuit Board 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 dynamic intermediate frequency selection for radio software anti-blocking interference, characterized in that, Includes the following steps: S1. Radio Frequency Signal Reception: Establish the received signal model of the PDT downlink, receive radio frequency signals and obtain discrete signal sequences; S2. Blocking Interference Detection and Decision: Based on the discrete signal sequence, frequency domain analysis is performed to calculate the energy statistical characteristics of a specific frequency band, and the results are compared with a preset decision threshold to determine whether there is blocking interference in the current channel, and a binary decision result is output. S3. Intermediate Frequency (IF) Configuration Selection: Dynamically configure the IF mode of the receiver based on the binary decision result; if the decision indicates no jamming interference, configure the receiver in zero IF mode; if the decision indicates jamming interference, configure the receiver in low IF mode. S4. Radio Frequency Signal Processing: Processing the selected intermediate frequency received signal: When the receiver is configured in low intermediate frequency mode, the low intermediate frequency received signal is down-converted to shift the useful signal to the baseband, while shifting the blocking interference to a higher frequency. S5. High-frequency suppression: The signal is filtered according to the current intermediate frequency mode; for zero intermediate frequency mode, a baseband low-pass filter is used; for low intermediate frequency mode, a low-pass filter is used to filter out the blocking interference located at the high frequency after down-conversion, so as to obtain the purified baseband signal.

2. The method according to claim 1, characterized in that, In step S2, determining whether there is blocking interference in the current channel specifically includes: S201. Calculate the power spectral density estimate of the discrete signal sequence; S202. Based on the Neyman-Pearson criterion, calculate the decision threshold according to the preset false alarm probability; S203. Calculate the ratio of energy in the target frequency band to energy in the entire frequency band as a detection statistic, and compare the statistic with the decision threshold to determine whether there is blocking interference.

3. The method according to claim 2, characterized in that, In step S202, the decision threshold Calculated using the following formula: ,in For the generalized Marcum Q function and These represent the expected value and variance under the null hypothesis, respectively. This represents the probability of a false alarm. It is the inverse function of the generalized Marcum Q function.

4. The method according to claim 1, characterized in that, In step S4, the downconversion process is achieved by multiplying the low-IF received signal with a complex conjugate low-IF local oscillator signal.

5. The method according to claim 1, characterized in that, In step S3, the intermediate frequency in the low-intermediate frequency mode It is configured to be half the bandwidth of the PDT signal.

6. The method according to claim 1, characterized in that, In step S5, the low-pass filter used for the low-intermediate frequency mode is a finite-length impulse response filter.

7. The method according to claim 6, characterized in that, The finite-length impulse response filter is designed using a Kaiser window.

8. A PDT terminal device based on dynamic intermediate frequency selection to resist jamming interference, characterized in that, include: The radio frequency receiving module is used to receive radio frequency signals and acquire discrete signal sequences; the interference detection and decision module is used to perform frequency domain analysis based on the discrete signal sequences, calculate the energy statistical characteristics of a specific frequency band, compare them with a preset decision threshold, determine whether there is blocking interference in the current channel, and output a binary decision result. The intermediate frequency (IF) configuration control module is used to dynamically configure the IF mode of the receiver according to the binary decision result; if the decision indicates no blocking interference, the receiver is configured to zero IF mode; if the decision indicates the presence of blocking interference, the receiver is configured to low IF mode. The signal processing module is used to down-convert the low IF received signal when the receiver is configured to low IF mode, shifting the useful signal to the baseband while simultaneously shifting the blocking interference to a higher frequency. The filtering module is used to filter the signal according to the current IF mode; for zero IF mode, a baseband low-pass filter is used; for low IF mode, a low-pass filter is used to filter out the blocking interference located at a high frequency after down-conversion, obtaining a purified baseband signal.

9. The device according to claim 8, characterized in that, The interference detection decision module is specifically used for: calculating the power spectral density estimate of the discrete signal sequence; calculating the decision threshold based on the Neyman-Pearson criterion and the preset false alarm probability; calculating the ratio of the target frequency band energy to the total frequency band energy as a detection statistic, and comparing it with the decision threshold to make a decision.

10. The device according to claim 8, characterized in that, The signal processing module achieves down-conversion by multiplying the low-IF received signal with a complex conjugate low-IF local oscillator signal.

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