Multi-channel integrated radio frequency system based on double-threshold interference detection and dynamic spectrum aggregation

Abstract

The invention discloses a multi-channel integrated radio frequency system based on double-threshold interference detection and dynamic spectrum aggregation. A radio frequency front-end unit is used for realizing broadband spectrum access and performing analog-to-digital conversion; the digital channel processing unit is used for realizing channelized segmentation through up-conversion and down-conversion, carrying out band elimination filtering to shield unavailable channels and outputting filtering parameters to support dynamic channel recombination; the digital signal parallel processing unit performs parallel access by using the divided channels; the spectrum sensing unit is used for carrying out double-threshold channel interference detection and real-time spectrum analysis according to the parallel access signals; and the frequency spectrum decision-making unit is used for judging the channel state and fusion detection judgment according to the interference detection result, judging the availability of a specific channel in the data link network and carrying out cooperative dynamic frequency spectrum aggregation. According to the method, a consistent spectrum access decision is realized by adopting a spectrum monitoring, sensing convergence and fusion decision mechanism, and consistent understanding of an available frequency set and high-reliability network domain dynamic spectrum aggregation are guaranteed.

Description

Technical Field

[0001] This invention relates to the field of military data link communication technology, and in particular to a multi-channel integrated radio frequency system based on dual-threshold interference detection and dynamic spectrum aggregation. Background Technology

[0002] Existing unmanned data link communication systems include V / UHF telemetry and control data links, C-band formation coordination links, and UHF / L-band unmanned broadband radios, primarily using a single operating frequency band for data link communication. When unmanned swarms approach enemy territory in formation to perform missions, they will face severe challenges from all-time frequency fixation, all-time frequency sweeping, wideband time-hopping interference, and even comb-like interference and full-band suppression interference. At this point, traditional single anti-jamming technologies are no longer sufficient to meet the needs of actual battlefield applications, and multi-dimensional anti-jamming technologies are required to cope with the challenges of complex electromagnetic interference.

[0003] The electromagnetic environment of modern battlefields is characterized by high complexity, high dynamism, and high adversarial nature. Wideband and intelligent anti-jamming technologies introduce machine learning and intelligent decision-making techniques into anti-jamming design, enabling communication systems to autonomously generate communication strategies based on changes in the electromagnetic environment. This fully utilizes multi-dimensional resources in the time domain, frequency domain, spatial domain, and polarization domain, thereby greatly enhancing the anti-jamming capabilities of communication systems.

[0004] Spectrum aggregation technology expands multiple discrete or continuous small frequency bands into a wider bandwidth for data transmission, thereby increasing system transmission rates. Spectrum aggregation technology mainly includes two approaches: physical layer aggregation and access layer aggregation. Physical layer spectrum aggregation (SA) technology simultaneously accesses multiple spectrum holes, aggregating discrete spectrum into a wider bandwidth, thus enabling high-speed transmission. MAC layer spectrum aggregation / channel aggregation supports greater bandwidth transmission by accessing multiple narrowband channels. Channel aggregation can solve compatibility issues while providing higher transmission bandwidth.

[0005] Due to limitations in RF front-end sampling rate, filter performance, and digital signal processor computing power, it is impractical to use a unified RF device to achieve physical layer spectrum aggregation and allocate any subcarrier within the entire bandwidth to a single user. Tunable filter banks are needed to achieve large-bandwidth, reconfigurable dynamic spectrum aggregation.

[0006] In existing data link communication processes, there are generally insufficient adaptability of single energy thresholds (such as only judging "occupied / idle"), inability to distinguish between natural background noise and man-made high-power interference, low interference tolerance, failure of fixed spectrum allocation strategies under enemy full-band suppression interference or comb spectrum interference, and inability to achieve dynamic spectrum aggregation. Summary of the Invention

[0007] Therefore, the purpose of this invention is to provide a multi-channel integrated radio frequency system based on dual-threshold interference detection and dynamic spectrum aggregation. By constructing a reconfigurable filter bank through analog + digital two-stage filters and a spectrum sensing decision unit, it can achieve the purpose of resisting partial band blocking interference and narrowband comb spectrum interference.

[0008] To achieve the above objectives, the present invention provides a multi-channel integrated radio frequency system based on dual-threshold interference detection and dynamic spectrum aggregation, comprising: The radio frequency front-end unit is used for broadband spectrum access and performs analog-to-digital conversion on the acquired signals; The digital channel processing unit achieves channel segmentation through up-conversion and down-conversion, performs band-stop filtering to shield unusable channels, and outputs filter parameters to support dynamic channel recombination. The digital signal parallel processing unit utilizes the segmented channels to perform parallel access to single-channel digital signals and / or multiple-channel digital signals; The spectrum sensing unit performs dual-threshold channel interference detection and real-time spectrum analysis based on parallel access signals. The spectrum decision unit determines the channel status based on the interference detection results, performs fusion detection and decision based on the spectrum detection results, determines the availability of a specific narrowband channel in the data link network communication system, and performs cooperative dynamic spectrum aggregation.

[0009] More preferably, the spectrum sensing unit performs dual-threshold channel interference detection and real-time spectrum analysis based on parallel access signals, including the following steps: S01. Perform power spectral density analysis on the incoming signal to obtain the power spectral density of the high-speed sampled signal; S02. Integrate the bandwidth based on the power spectral density to obtain the energy value of the specific channel; S03. Based on the energy value of the specific channel, perform background noise energy detection based on the background noise threshold; S04. Interference signal energy detection is performed only after the energy value exceeds the background noise threshold.

[0010] More preferably, the power spectral density analysis of the accessed signal includes calculating the power spectral density of the high-speed sampled signal using the following formula (1): (1) In the formula, Let x(t) be the amplitude spectrum. Let x(t) be the power spectral density. Indicates the signal Perform a Fast Fourier Transform.

[0011] More preferably, in S2, when integrating the bandwidth based on the power spectral density to obtain the energy value of a specific channel, the following formula is used: in, Let B be the energy level of the i-th narrowband channel, and B be the channel bandwidth. Let x(t) be the power spectral density of the signal.

[0012] More preferably, in S3, when performing background noise energy detection based on a background noise threshold, the following formula is used to determine whether the channel is idle: (3) Background noise threshold: (4) In the formula, Let k be the state of the i-th narrowband channel, k be the Boltzmann constant, T be the noise temperature, and B be the channel bandwidth. Noise figure Indicates that the channel is idle. This indicates a weak interference channel.

[0013] In a further preferred embodiment, in S4, when the energy value exceeds the background noise threshold, the interference signal energy is detected using the following formula (5): (5) (6) In the formula, To demodulation threshold, For the signal-to-weight ratio threshold. This indicates a strong interference channel.

[0014] More preferably, when the spectrum sensing unit performs real-time spectrum analysis, it further includes: obtaining the power spectral density estimate of the signal using the Burg power spectral density estimation method based on linear predictive analysis. An autoregressive model was established based on the real-time spectrum. ; The autoregressive model is solved by the minimum mean square error criterion to obtain the estimated values ​​of the autoregressive coefficients and noise variance. Based on the autoregressive model, the power spectral density estimate of the signal is obtained: in, These are the autoregressive coefficients. For noise item This represents the noise variance.

[0015] Further preferred methods include system setup using the following process: S11. Initialize the time-frequency resources, the initialization including allocating time slot resources and configuring basic channel parameters; S12. Configure the working mode switching strategy, including: In time division multiple access mode, link control is performed, which includes time slot scheduling and working mode switching according to the time slot table; In normal communication mode, the system performs digital channelization processing and parallel processing of multiple signals, providing physical layer transmission services to the upper layer. In radio silence mode, the multi-channel integrated radio frequency system disables communication functions. With the assistance of preprocessing by the digital channelization processing unit, it performs spectrum sensing and spectrum decision-making, and performs dynamic spectrum aggregation and parameter configuration of reconfigurable digital filters based on the spectrum decision results.

[0016] More preferably, in radio silence mode, when performing fusion detection and decision based on spectrum detection results to determine the availability of a specific narrowband channel in the data link network communication system, and when performing cooperative dynamic spectrum aggregation, the following are included: After interference detection, the N channels in the wideband form three frequency sets based on their states: idle channels, weak interference channels, and strong interference channels. The OR merging criterion, AND merging criterion, or K-rank merging criterion are used to dynamically aggregate the spectrum of discontinuous idle channel sets to form an idle spectrum. The set of discontinuous weak interference channels is dynamically aggregated to form a usable spectrum, which can support spread spectrum modulation, low code rate, and low data transmission. Discontinuous, high-interference channels are considered unusable channels, and band-stop filtering is applied to them.

[0017] A further preferred embodiment includes updating the digital filter bank based on the dynamic spectrum aggregation results, filtering out unusable channels through digital stopband filters, and reducing signal processing on unusable channels.

[0018] The multi-channel integrated radio frequency system disclosed in this application, based on dual-threshold interference detection and dynamic spectrum aggregation, performs dynamic parameter configuration of the wireless channel through the output signal of the spectrum sensing decision unit. The latter uses a dual-threshold frequency domain interference detection and cooperative dynamic spectrum aggregation method to perform broadband spectrum sensing and discontinuous spectrum access decision, and has broadband dynamic spectrum aggregation function.

[0019] The dual-threshold frequency domain interference detection method proposed in this application uses noise threshold and interference-to-signal ratio threshold for dual-threshold energy detection based on real-time spectrum analysis. It supports the identification of strong interference, weak interference, and idle channels, enabling spectrum decision-making to support multi-mode spectrum aggregation, and supporting interference channel shielding, low-speed transmission, and high-speed transmission respectively.

[0020] This application adopts a collaborative dynamic spectrum aggregation method, which uses spectrum monitoring, sensing convergence and fusion decision-making mechanisms to achieve consistent spectrum access decisions, ensure consistent understanding of available frequency sets and highly reliable dynamic spectrum aggregation in the network domain, and support adaptive frequency hopping communication in data link communication systems. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the structure of the multi-channel integrated radio frequency system provided by the present invention.

[0022] Figure 2 This is a time slot resource allocation diagram in this invention.

[0023] Figure 3 This is a flowchart of the dual-threshold frequency domain interference detection process of the present invention.

[0024] Figure 4 This is a flowchart of the collaborative dynamic spectrum aggregation processing in this invention. Detailed Implementation

[0025] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0026] like Figure 1 As shown, one embodiment of the present invention provides a multi-channel integrated radio frequency system based on dual-threshold interference detection and dynamic spectrum aggregation. This system constructs a reconfigurable filter bank through a two-stage analog + digital filter and a spectrum sensing decision unit, achieving the purpose of resisting partial-band blocking interference and narrowband comb spectrum interference. It includes five parts: multiple sets of radio frequency front-end and antenna units, a digital channel processing unit, a digital signal parallel processing unit, a spectrum sensing unit, and a spectrum decision unit.

[0027] The radio frequency front-end unit is used for broadband spectrum access and analog-to-digital conversion of the acquired signals. It includes multiple radio frequency front-ends and antennas, and selects and designs components and modules according to wavelength to realize broadband spectrum access function, covering different operating frequency bands in the range of 0~6GHz, such as HF, VHF, UHF, L band, S band, C band, etc.

[0028] Each RF front-end module consists of functional units such as analog filter banks, power amplifiers, low-noise amplifiers, and transceivers. Among them, the analog filter bank is a key component determining the frequency domain performance of the RF front-end; its bandpass and stopband characteristics determine the bandwidth, frequency flatness, and adjacent channel rejection, among other RF parameters. The power amplifier amplifies the transmitted signal and is a key component determining the transmitter's signal power level and power efficiency. The low-noise amplifier amplifies the received signal after bandpass filtering and is a key component determining the receiver's sensitivity and noise figure. The wireless transceiver is the signal conversion unit of the transceiver, primarily performing analog-to-digital and digital-to-analog conversion functions.

[0029] After AD conversion, the RF front-end module transmits the wideband high-speed sampling signal to the digital channel processing unit via a high-speed data bus for channelization processing in the digital domain.

[0030] The digital channel processing unit achieves channel segmentation through up-conversion and down-conversion, performs band-stop filtering to shield unusable channels, and outputs filter parameters to support dynamic channel recombination. The digital channel processing unit downsamples and frequency-shifts the broadband signal based on polyphase filtering in the digital domain, forming multiple narrowband channels. The digital channel processing unit consists of functional components such as digital up-conversion, digital down-conversion, digital filtering, and digital channelization processing.

[0031] The digital upconversion component performs digital mixing via a digital frequency synthesizer, shifting the frequency of the digital intermediate frequency (IF) signal to the radio frequency (RF) frequency. The digital downconversion component performs digital mixing via a digital frequency synthesizer, shifting the high-frequency signal to the IF or baseband signal.

[0032] Digital filter banks employ polyphase filtering principles to convert ultra-wideband channels to narrowband channels, forming multiple narrowband phase-shift channels. The digital filter bank also includes band-stop filtering units to shield unusable channels, preventing them from participating in digital up-conversion and down-conversion processing.

[0033] The digital channelization processing component supports reconfigurable digital filtering in the dynamic spectrum aggregation output parameter configuration. By externally configuring bandpass and bandstop filter parameters, it supports subband filtering and dynamic channel reconfiguration functions.

[0034] The digital signal parallel processing unit utilizes the segmented channels to perform parallel access to single-channel and / or multiple-channel digital signals; it supports parallel processing of single-channel and / or multiple-channel digital signals, including baseband signal processing functions such as symbol processing, code block processing, channel encoding and decoding, and modulation and demodulation.

[0035] In the frequency hopping transmission mechanism, the digital signal processing unit also supports the joint processing of multiple data pulses, including pulse interleaving coding, joint channel estimation and other processing functions.

[0036] The digital signal parallel processing unit enhances the broadband parallel signal processing capability and data throughput of the multi-channel integrated RF system, enabling the multi-channel integrated RF system to support large-bandwidth signal processing after continuous or discontinuous spectrum aggregation.

[0037] The spectrum sensing unit performs dual-threshold channel interference detection and real-time spectrum analysis based on parallel access signals; it is used to detect wideband spectrum occupancy and spectral holes. More preferably, the spectrum sensing unit, when performing dual-threshold channel interference detection and real-time spectrum analysis based on parallel access signals, includes the following steps: the real-time spectrum analysis can be performed using a spectrum analysis method based on Fast Fourier Transform (FFT) or Linear Prediction (LSP) to obtain the power spectral density of the wideband signal.

[0038] like Figure 3 As shown, the specific steps include S01, performing power spectral density analysis on the input signal to obtain the power spectral density of the high-speed sampling signal; More preferably, the power spectral density analysis of the accessed signal includes calculating the power spectral density of the high-speed sampled signal using the following formula (1): (1) In the formula, Let x(t) be the amplitude spectrum. Let x(t) be the power spectral density. Indicates the signal Perform a Fast Fourier Transform.

[0039] The spectrum sensing unit, when performing real-time spectrum analysis, also includes: obtaining the power spectral density estimate of the signal using the Burg power spectral density estimation method based on linear predictive analysis. An autoregressive model was established based on the real-time spectrum. ; The autoregressive model is solved by the minimum mean square error criterion to obtain the estimated values ​​of the autoregressive coefficients and noise variance. Based on the autoregressive model, the power spectral density estimate of the signal is obtained: in, These are the autoregressive coefficients. For noise item This represents the noise variance.

[0040] S02. Integrate the bandwidth based on the power spectral density to obtain the energy value of the specific channel; The energy value of a specific channel is obtained by integrating the bandwidth based on the power spectral density using the following formula: in, Let B be the energy level of the i-th narrowband channel, and B be the channel bandwidth. Let x(t) be the power spectral density of the signal.

[0041] S03. Based on the energy value of the specific channel, perform background noise energy detection based on the background noise threshold; When performing background noise energy detection based on a background noise threshold, the following formula is used to determine whether the channel is idle: (3) Background noise threshold: (4) In the formula, Let k be the state of the i-th narrowband channel, k be the Boltzmann constant, T be the noise temperature, and B be the channel bandwidth. Noise figure Indicates that the channel is idle. This indicates a weak interference channel.

[0042] S04. Interference signal energy detection is performed only after the energy value exceeds the background noise threshold.

[0043] When the energy value exceeds the background noise threshold, the interference signal energy is detected using the following formula (5): (5) (6) In the formula, To demodulation threshold, For the signal-to-weight ratio threshold. This indicates a strong interference channel.

[0044] The spectrum decision unit determines the channel status based on the interference detection results, performs fusion detection and decision based on the spectrum detection results, determines the availability of a specific narrowband channel in the data link network communication system, and performs cooperative dynamic spectrum aggregation.

[0045] Based on interference detection results, the channel state is determined; based on spectrum detection results, a fusion detection decision is made to determine the availability of a specific narrowband channel in the data link network communication system; and further optimization is performed through cooperative dynamic spectrum aggregation. This also includes system configuration using the following process: Figure 4 As shown: S11. Initialize the time-frequency resources, the initialization including allocating time slot resources and configuring basic channel parameters; S12. Configure the working mode switching strategy, including: Link control is performed in time-division multiple access mode, including time slot scheduling and operating mode switching based on a time slot table; the time slot table is as follows: Figure 2 As shown.

[0046] In normal communication mode, the system performs digital channelization processing and parallel processing of multiple signals, providing physical layer transmission services to the upper layer. In radio silence mode, the multi-channel integrated radio frequency system disables communication functions. With the assistance of preprocessing by the digital channelization processing unit, it performs spectrum sensing and spectrum decision-making, and performs dynamic spectrum aggregation and parameter configuration of reconfigurable digital filters based on the spectrum decision results.

[0047] Furthermore, in radio silence mode, when performing fusion detection decisions based on spectrum detection results to determine the availability of a specific narrowband channel in the data link network communication system, and when performing cooperative dynamic spectrum aggregation, the following steps are included: After interference detection, the N channels in the wideband form three frequency sets based on their states: idle channels, weak interference channels, and strong interference channels. Using the OR merging criterion, AND merging criterion, or K-rank merging criterion, the discontinuous set of idle channels is dynamically aggregated to form an idle spectrum. After receiving the frequency sensing information aggregated from each node, the master node needs to merge the sensing information to remove unusable frequencies in the current frequency hopping pattern or restore the normal use of previously removed frequencies. Commonly used fusion decision mechanisms include the OR merging criterion, the AND merging criterion, and the K-rank merging criterion.

[0048] The OR merging criterion is that unless all sensing nodes determine that a frequency point is unavailable, the information fusion center will ultimately determine that the frequency point is available. That is, as long as one node thinks that the frequency point is available, the fusion center will determine that the frequency point is available.

[0049] The AND merging criterion is that unless all sensing nodes determine that a frequency point is available, the information fusion center will ultimately determine that the frequency point is unavailable. That is, as long as one node thinks that the frequency point is unavailable, the fusion center will determine that the frequency point is unavailable.

[0050] The K-rank merging criterion is as follows: a frequency point is considered usable only when the number of usable nodes is greater than or equal to K (K is generally not less than half the number of network nodes); or in multi-bit quantization, a frequency point is considered usable only when the quantization value of all nodes in a frequency point is less than K (here, the value of K is related to both the number of nodes and the quantization bit width, and the larger the value, the greater the interference).

[0051] The K-rank merging criterion is quite flexible. By removing the maximum and minimum values ​​of K, it becomes the AND and OR merging criteria, respectively. In this design, the K-rank merging criterion is adopted, and the value of K can be flexibly configured.

[0052] The set of discontinuous weak interference channels is dynamically aggregated to form a usable spectrum, which can support spread spectrum modulation, low code rate, and low data transmission.

[0053] Discontinuous, high-interference channels are considered unusable channels, and band-stop filtering is applied to them.

[0054] A further preferred embodiment includes updating the digital filter bank based on the dynamic spectrum aggregation results, filtering out unusable channels through digital stopband filters, and reducing signal processing on unusable channels.

[0055] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A multi-channel integrated radio frequency system based on dual-threshold interference detection and dynamic spectrum aggregation, characterized in that, include: The radio frequency front-end unit is used for broadband spectrum access and performs analog-to-digital conversion on the acquired signals; The digital channel processing unit achieves channel segmentation through up-conversion and down-conversion, performs band-stop filtering to shield unusable channels, and outputs filter parameters to support dynamic channel recombination. The digital signal parallel processing unit utilizes the segmented channels to perform parallel access to single-channel digital signals and / or multiple-channel digital signals; The spectrum sensing unit performs dual-threshold channel interference detection and real-time spectrum analysis based on parallel access signals. The spectrum decision unit determines the channel status based on the interference detection results, performs fusion detection and decision based on the spectrum detection results, determines the availability of a specific narrowband channel in the data link network communication system, and performs cooperative dynamic spectrum aggregation.

2. The multi-channel integrated radio frequency system based on dual-threshold interference detection and dynamic spectrum aggregation according to claim 1, characterized in that, The spectrum sensing unit performs dual-threshold channel interference detection and real-time spectrum analysis based on parallel access signals, including the following steps: S01. Perform power spectral density analysis on the incoming signal to obtain the power spectral density of the high-speed sampled signal; S02. Integrate the bandwidth based on the power spectral density to obtain the energy value of the specific channel; S03. Based on the energy value of the specific channel, perform background noise energy detection based on the background noise threshold; S04. Interference signal energy detection is performed only after the energy value exceeds the background noise threshold.

3. The multi-channel integrated radio frequency system based on dual-threshold interference detection and dynamic spectrum aggregation according to claim 2, characterized in that, The power spectral density analysis of the input signal includes calculating the power spectral density of the high-speed sampled signal using the following formula (1): (1) In the formula, Let x(t) be the amplitude spectrum. Let x(t) be the power spectral density. Indicates the signal Perform a Fast Fourier Transform.

4. The multi-channel integrated radio frequency system based on dual-threshold interference detection and dynamic spectrum aggregation according to claim 2, characterized in that, In S02, the energy value of a specific channel is obtained by bandwidth integration based on the power spectral density using the following formula: in, Let B be the energy level of the i-th narrowband channel, and B be the channel bandwidth. Let x(t) be the power spectral density of the signal.

5. The multi-channel integrated radio frequency system based on dual-threshold interference detection and dynamic spectrum aggregation according to claim 2, characterized in that, In S03, when performing background noise energy detection based on a background noise threshold, the following formula is used to determine whether the channel is idle: (3) Background noise threshold: (4) In the formula, Let k be the state of the i-th narrowband channel, k be the Boltzmann constant, T be the noise temperature, and B be the channel bandwidth. Noise figure Indicates that the channel is idle. This indicates a weak interference channel.

6. The multi-channel integrated radio frequency system based on dual-threshold interference detection and dynamic spectrum aggregation according to claim 2, characterized in that, In S04, when the energy value exceeds the background noise threshold, the interference signal energy is detected using the following formula (5): (5) (6) In the formula, To demodulation threshold, For the signal-to-weight ratio threshold. This indicates a strong interference channel.

7. The multi-channel integrated radio frequency system based on dual-threshold interference detection and dynamic spectrum aggregation according to claim 1, characterized in that, The spectrum sensing unit, when performing real-time spectrum analysis, also includes: obtaining the power spectral density estimate of the signal using the Burg power spectral density estimation method based on linear predictive analysis. An autoregressive model was established based on the real-time spectrum. ; The autoregressive model is solved by the minimum mean square error criterion to obtain the estimated values ​​of the autoregressive coefficients and noise variance. Based on the autoregressive model, the power spectral density estimate of the signal is obtained: in, These are the autoregressive coefficients. For noise item This represents the noise variance.

8. The multi-channel integrated radio frequency system based on dual-threshold interference detection and dynamic spectrum aggregation according to claim 1, characterized in that, This also includes system setup using the following process: S11. Initialize the time-frequency resources, the initialization including allocating time slot resources and configuring basic channel parameters; S12. Configure the working mode switching strategy, including: In time division multiple access mode, link control is performed, which includes time slot scheduling and working mode switching according to the time slot table; In normal communication mode, the system performs digital channelization processing and parallel processing of multiple signals, providing physical layer transmission services to the upper layer. In radio silence mode, the multi-channel integrated radio frequency system disables communication functions. With the assistance of preprocessing by the digital channelization processing unit, it performs spectrum sensing and spectrum decision-making, and performs dynamic spectrum aggregation and parameter configuration of reconfigurable digital filters based on the spectrum decision results.

9. The multi-channel integrated radio frequency system based on dual-threshold interference detection and dynamic spectrum aggregation according to claim 1, characterized in that, When performing cooperative dynamic spectrum aggregation based on spectrum detection results to determine the availability of a specific narrowband channel in a data link network communication system, the following steps are included: After interference detection, the N channels in the broadband are divided into three frequency sets based on their states: idle channels, weak interference channels, and strong interference channels. The OR merging criterion, AND merging criterion, or K-rank merging criterion are used to dynamically aggregate the spectrum of discontinuous idle channel sets to form an idle spectrum; The set of discontinuous weak interference channels is dynamically aggregated to form a usable spectrum, which can support spread spectrum modulation, low code rate, and low data transmission. Discontinuous, highly interfering channels are considered unusable channels, and band-stop filtering is applied to them.

10. The multi-channel integrated radio frequency system based on dual-threshold interference detection and dynamic spectrum aggregation according to claim 9, characterized in that, It also includes updating the digital filter bank based on the results of dynamic spectrum aggregation, filtering out signals through digital stopband filters, and reducing signal processing on unusable channels.

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