Communication method and system for signals in slowly changing complex environment

Abstract

The present invention provides a communication method and system for signals in a slowly varying complex environment, comprising: a communication signal design step: a signal source transmits a single-frequency sinusoidal signal through a channel in a slowly varying complex environment for transmission, which is received by a signal destination, and a single-frequency sinusoidal signal time slice and a time division multiplexing time slice of a signal to be transmitted are designed; a channel estimation step: a signal source transmits a single-frequency sinusoidal signal slice, which is transmitted through a channel in a slowly varying complex environment, which is received by a signal destination, and tap coefficients that can converge to the environment are obtained, and a noise power spectrum of the slowly varying complex environment is calculated; a spectrum shifting step: a modulation frequency of a transmission signal is adjusted using a noise power spectrum, the signal source transmits the adjusted transmission signal, which is transmitted through a channel in a slowly varying complex environment, and is received by a signal destination; a transmission signal identification step: a spectrum analysis is performed on the noise power spectrum and the modulation frequency; and a result step: the channel estimation step to the transmission signal identification step are repeatedly executed.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a method and system for communicating signals in a slowly changing complex environment. Background Art

[0002] In the field of communications, communication in complex environments is a challenging and realistic research issue. For communications in complex environments, it is of great significance to be able to achieve communication and interference suppression under extremely low signal-to-interference ratio and slowly varying non-steady-state background noise conditions, and to improve the sensitivity of the receiver.

[0003] The existing technical solutions have the following technical defects: the receiver design through channel modeling is difficult to track the noise changes of time-varying complex channels, and can only be designed for specific channels to achieve interference suppression, which is not applicable to complex environments and unknown channels.

[0004] Compared with the Wiener filter that requires prior knowledge of noise and the Kalman filter that requires iterative estimation of model parameters, the minimum mean square adaptive filter can complete filtering without prior knowledge. The background noise is stable noise. The minimum mean square adaptive filter can converge to the optimal Wiener solution after successful iteration to achieve filtering. In a slowly changing non-stationary environment, the minimum mean square adaptive filter can achieve real-time tracking. The minimum mean square adaptive filter is scalable and can improve the algorithm according to the requirements of specific scenarios (such as some additional algorithms, or the design of step size and number of taps), making it targeted and special. Summary of the invention

[0005] In view of the defects in the prior art, the present invention provides a method and system for communicating signals in a slowly changing complex environment.

[0006] According to a method and system for communicating signals in a slowly changing complex environment provided by the present invention, the scheme is as follows:

[0007] In a first aspect, a method for communicating signals in a slowly changing complex environment is provided, the method comprising:

[0008] Communication signal design steps: Use a single-frequency sinusoidal signal to transmit through a channel in a slowly varying complex environment, receive it at the destination, and use the single-frequency sinusoidal signal time slice as a reference and the time division multiplexing time slice of the signal to be transmitted based on the convergence of the tap coefficients of the least mean square adaptive filter;

[0009] Channel estimation step: using the single-frequency sinusoidal signal time slice to transmit through the channel in a slowly varying complex environment, receiving at the destination, obtaining the tap coefficients that can converge to the environment through least mean square adaptive filtering, and calculating the noise power spectrum of the slowly varying complex environment based on the tap coefficients;

[0010] Spectrum shifting step: using the noise power spectrum to adjust the modulation frequency of the transmission signal, transmitting it through a channel in a slowly changing complex environment, and receiving it at the destination;

[0011] Transmission signal identification step: performing spectrum analysis according to the noise power spectrum and modulation frequency to achieve transmission signal identification;

[0012] Result step: Repeat the channel estimation step to the transmission signal identification step to achieve signal communication in a complex environment.

[0013] Preferably, the communication signal design step comprises:

[0014] Step S1.1: Select a single-frequency sinusoidal signal, pass it through a slowly changing complex environment, and measure it after it is received at the destination to obtain the measured value at each moment;

[0015] Step S1.2: Adopting the least mean square adaptive filtering, taking the single-frequency sinusoidal signal as the reference signal and the measured value as the input signal, and performing adaptive filtering;

[0016] Step S1.3: by setting the error threshold, the convergence time and the convergence duration of the slowly changing complex environment are obtained;

[0017] Step S1.4: Design the single-frequency sinusoidal signal time slice and the time division multiplexing time slice of the transmission signal according to the convergence time and the convergence duration.

[0018] Preferably, the step S1.4 comprises: adopting the minimum mean square error criterion and setting a threshold of the minimum mean square error of the adaptive filter as a criterion for judging whether the filter has converged;

[0019] In time slicing, it is divided into a single-frequency sinusoidal signal, a transmission signal and a mark for distinguishing the single-frequency sinusoidal signal and the transmission signal. The duration of the single-frequency sinusoidal signal should be greater than or equal to the minimum mean square adaptive filter convergence time, and the duration of the transmission signal mark should be less than or equal to the time that the environment can make the minimum mean square adaptive filter converge.

[0020] Preferably, the channel estimation step comprises:

[0021] Step S2.1: adopting the least mean square adaptive filtering, taking the single-frequency sinusoidal signal time slice as the reference signal, taking the single-frequency sinusoidal signal received by the sink through the slowly varying complex environment as the input signal, and obtaining the convergence coefficient of the least mean square adaptive filter;

[0022] Step S2.2: Calculate the noise power spectrum of the slowly varying complex environment at that moment according to the obtained tap coefficients of the least mean square adaptive filter.

[0023] Preferably, the spectrum shifting step comprises:

[0024] Step S3.1: determining a frequency band suitable for signal transmission according to the noise power spectrum, that is, a frequency band with a lower noise spectrum amplitude, and informing the signal source;

[0025] Step S3.2: The information source performs carrier modulation on the transmitted signal and moves the modulated signal to the frequency band.

[0026] Preferably, the transmission signal identification step comprises:

[0027] Step S4.1: The modulated signal is time-sliced ​​as a transmission signal and transmitted via a channel in a slowly varying complex environment, and received at a destination;

[0028] Step S4.2: Bandpass filter the measurement results according to the frequency of the transmission signal to obtain the signal and the narrowband interference with low amplitude, and perform window Fourier transform to obtain the spectrum. Use spectral subtraction to subtract the noise spectrum of the background noise in the corresponding time period to realize the identification of the transmission signal.

[0029] In a second aspect, a communication system for signals in a slowly changing complex environment is provided, the system comprising:

[0030] Communication signal design module: Use a single-frequency sinusoidal signal to transmit through a channel in a slowly changing complex environment, receive it at the destination, and use the single-frequency sinusoidal signal time slice as a reference and the time division multiplexing time slice of the signal to be transmitted according to the convergence of the tap coefficients of the least mean square adaptive filter;

[0031] Channel estimation module: using the single-frequency sinusoidal signal time slices, transmitting through the channel in a slowly varying complex environment, receiving at the destination, obtaining the tap coefficients that can converge to the environment through least mean square adaptive filtering, and calculating the noise power spectrum of the slowly varying complex environment based on this;

[0032] Spectrum shifting module: uses the noise power spectrum to adjust the modulation frequency of the transmission signal, transmits it through a channel in a slowly changing complex environment, and receives it at the destination;

[0033] Transmission signal identification module: performs spectrum analysis according to the noise power spectrum and modulation frequency to realize transmission signal identification;

[0034] Result module: Repeat the channel estimation step to the transmission signal identification step to achieve signal communication in complex environments.

[0035] Preferably, the communication signal design module includes:

[0036] Module M1.1: Select a single-frequency sinusoidal signal, pass it through a slowly changing complex environment, and measure it after it is received by the destination to obtain the measured value at each moment;

[0037] Module M1.2: adopting the least mean square adaptive filtering, taking the single-frequency sinusoidal signal as the reference signal and the measured value as the input signal, and performing adaptive filtering;

[0038] Module M1.3: By setting the error threshold, the convergence time and convergence duration of the slowly changing complex environment are obtained;

[0039] Module M1.4: Design single-frequency sinusoidal signal time slices and time-division multiplexing time slices of transmission signals according to convergence time and convergence duration;

[0040] The module M1.4 includes: adopting the minimum mean square error criterion and setting the threshold of the minimum mean square error of the adaptive filter as a criterion for judging whether it has converged;

[0041] In time slicing, it is divided into a single-frequency sinusoidal signal, a transmission signal and a mark for distinguishing the single-frequency sinusoidal signal and the transmission signal. The duration of the single-frequency sinusoidal signal should be greater than or equal to the minimum mean square adaptive filter convergence time, and the duration of the transmission signal mark should be less than or equal to the time that the environment can make the minimum mean square adaptive filter converge.

[0042] Preferably, the channel estimation module comprises:

[0043] Module M2.1: adopts the minimum mean square adaptive filtering, takes the single-frequency sinusoidal signal time slice as the reference signal, takes the single-frequency sinusoidal signal received by the sink through the slowly varying complex environment as the input signal, and obtains the convergence coefficient of the minimum mean square adaptive filter;

[0044] Module M2.2: Calculate the noise power spectrum of the slowly varying complex environment at that moment according to the obtained tap coefficients of the least mean square adaptive filter.

[0045] Preferably, the spectrum shifting module includes:

[0046] Module M3.1: Determine the frequency band suitable for signal transmission according to the noise power spectrum, that is, the frequency band with lower noise spectrum amplitude, and inform the signal source;

[0047] Module M3.2: The signal source performs carrier modulation on the transmitted signal and moves the modulated signal to the frequency band;

[0048] The transmission signal identification step comprises:

[0049] Module M4.1: The modulated signal is time-sliced ​​as a transmission signal and transmitted through a channel in a slowly varying complex environment, and received at the destination;

[0050] Module M4.2: Bandpass filter the measurement results according to the frequency of the transmission signal to obtain the signal and the narrowband interference with low amplitude, and perform window Fourier transform to obtain the spectrum. Use spectral subtraction to subtract the noise spectrum of the background noise in the corresponding time period to realize the identification of the transmission signal.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] 1. The present invention has a reasonable structure and is easy to use. It can overcome the defects of the prior art and realize communication under the condition of slowly changing non-steady-state background noise;

[0053] 2. The present invention tracks changes in complex environments through adaptive filtering, can estimate time-varying complex channels under extremely low signal-to-noise ratio conditions, and achieve interference suppression, further improving the sensitivity of the receiver;

[0054] 3. The present invention can realize adaptive spectrum shifting of transmission signals according to the measured interference spectrum, determine the frequency band suitable for transmission, avoid the noise frequency band, further realize interference suppression, and improve the sensitivity of the receiver;

[0055] 4. The present invention has a wide range of applications, and the transmission signals include but are not limited to analog signals, digital signals, etc.; by combining with coding technology and other means, the communication performance can be further improved.

[0056] Other beneficial effects of the present invention will be explained in the specific implementation manner through the introduction of specific technical features and technical solutions. Through the introduction of these technical features and technical solutions, those skilled in the art should be able to understand the beneficial technical effects brought about by the technical features and technical solutions. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0058] Figure 1 It is a schematic diagram of the principle of the present invention;

[0059] Figure 2 Schematic diagram of communication signals of the present invention. DETAILED DESCRIPTION

[0060] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0061] The embodiment of the present invention provides a communication method and system for signals in a slowly changing complex environment, which uses the least mean square adaptive filtering to track in real time and perform time division multiplexing and time slicing. The present invention also obtains the interference spectrum of the unknown complex environment, and then adaptively shifts the spectrum of the unknown signal to place it behind the spectrum band with a lower background noise amplitude, and uses spectrum subtraction to achieve interference suppression and unknown signal identification. Figure 1 As shown, the present invention provides a method for realizing unknown signal identification under extremely low signal-to-interference ratio and slowly varying non-steady-state background noise conditions, and the method is specifically as follows:

[0062] Communication signal design steps: The source transmits a single-frequency sinusoidal signal through a slowly varying complex channel and receives it at the destination, i.e., the receiver. The signal is then filtered according to the convergence of the tap coefficients of the least mean square adaptive filter. Figure 2 As shown, a single-frequency sinusoidal signal used as a reference and a time slice of a time-division multiplexed signal to be transmitted are designed.

[0063] Specifically, the communication signal design step includes:

[0064] Step 1.1: Select a single-frequency sinusoidal signal, pass through a complex environment, and measure it after it is received at the destination to obtain the measured values ​​at each moment.

[0065] Step 1.2: Adopt the least mean square adaptive filtering, take the above single frequency signal as the reference signal and the measured value as the input signal, and perform adaptive filtering.

[0066] Step 1.3: By setting the error threshold, the convergence time and convergence duration of the slowly changing complex environment are obtained.

[0067] Step 1.4: Design the time slice of the time division multiplexing of the single frequency sinusoidal signal and the transmission signal according to the convergence time and the convergence duration.

[0068] The minimum mean square error criterion is adopted, and the threshold of the minimum mean square error of the adaptive filter is set as the criterion for whether it converges. Figure 2 As shown, in the time slice, it is divided into a single-frequency sinusoidal signal, a transmission signal and a marker for distinguishing the single-frequency sinusoidal signal from the transmission signal. The duration of the single-frequency sinusoidal signal should be greater than or equal to the minimum mean square adaptive filter convergence time, and the duration of the marker before the transmission signal machine should be less than or equal to the time that the environment can make the minimum mean square adaptive filter converge.

[0069] Channel estimation steps: The signal source transmits a single-frequency sinusoidal signal fragment, which is transmitted through the channel in a slowly varying complex environment and received by the receiver. The tap coefficients that can converge to the environment are obtained through the least mean square adaptive filtering module. The signal processing module calculates the noise power spectrum of the slowly varying environment based on this.

[0070] The channel estimation step specifically includes:

[0071] Step 2.1: Adopting the least mean square adaptive filtering, taking the time-sliced ​​single-frequency sinusoidal signal as the reference signal and the single-frequency sinusoidal signal received by the sink through the complex environment as the input signal, the convergence coefficient of the least mean square adaptive filter is obtained.

[0072] Step 2.2: Calculate the noise power spectrum of the slowly varying complex environment at that moment according to the obtained tap coefficients of the least mean square adaptive filter.

[0073] Spectrum shifting steps: The carrier frequency control module uses the above noise power spectrum to adjust the modulation frequency of the transmission signal. The signal source transmits the adjusted transmission signal, which is transmitted through the channel in a slowly changing complex environment and received by the receiver.

[0074] The spectrum transfer steps specifically include:

[0075] Step 3.1: Determine the frequency band suitable for signal transmission based on the obtained noise power spectrum, that is, the frequency band with lower noise spectrum amplitude, and inform the signal source.

[0076] Step 3.2: The signal source performs carrier modulation on the signal to be transmitted and moves the modulated signal to the above frequency band.

[0077] Transmission signal identification step: Based on the obtained noise power spectrum and the frequency of the adjusted transmission signal, after the receiver receives it, the signal processing module performs spectrum analysis to realize signal communication in complex environments.

[0078] The transmission signal identification step specifically includes:

[0079] Step 4.1: The modulated signal is time-sliced ​​as a transmission signal and transmitted through a channel in a slowly varying complex environment, and received at the destination.

[0080] Step 4.2: Bandpass filter the measurement results according to the frequency of the transmission signal to obtain the signal and the narrowband interference with low amplitude, and perform window Fourier transform to obtain the spectrum. Use spectral subtraction to subtract the noise spectrum of the background noise in the corresponding time period to realize the identification of the transmission signal.

[0081] Result step: Repeat the channel estimation step to the transmission signal identification step to achieve signal communication in a complex environment.

[0082] The present invention also provides a communication system for signals in a slowly changing complex environment, which can be implemented by executing the process steps of the communication method for signals in a slowly changing complex environment, that is, those skilled in the art can understand the communication method for signals in a slowly changing complex environment as a preferred implementation of the communication system for signals in a slowly changing complex environment. The system specifically includes the following contents:

[0083] Communication signal design module: Use a single-frequency sinusoidal signal to transmit through a channel in a slowly varying complex environment, receive it at the destination, and use the single-frequency sinusoidal signal time slice as a reference and the time division multiplexing time slice of the signal to be transmitted based on the convergence of its tap coefficients through the least mean square adaptive filter.

[0084] Channel estimation module: Use single-frequency sinusoidal signal time slices to transmit through the channel in a slowly varying complex environment, receive at the destination, and use minimum mean square adaptive filtering to obtain the tap coefficients that can converge to the environment, and calculate the noise power spectrum of the slowly varying complex environment based on this.

[0085] Spectrum shifting module: uses the noise power spectrum to adjust the modulation frequency of the transmission signal, transmits it through the channel in a slowly changing complex environment, and receives it at the destination.

[0086] Transmission signal identification module: performs spectrum analysis according to the noise power spectrum and modulation frequency to realize transmission signal identification.

[0087] Result module: Repeat the channel estimation step to the transmission signal identification step to achieve signal communication in complex environments.

[0088] Specifically, the communication signal design module includes:

[0089] Module M1.1: Select a single-frequency sinusoidal signal, pass it through a slowly changing complex environment, and measure it after it is received by the destination to obtain the measured value at each moment;

[0090] Module M1.2: adopting the least mean square adaptive filtering, taking the single-frequency sinusoidal signal as the reference signal and the measured value as the input signal, and performing adaptive filtering;

[0091] Module M1.3: By setting the error threshold, the convergence time and convergence duration of the slowly changing complex environment are obtained;

[0092] Module M1.4: Design single-frequency sinusoidal signal time slices and time-division multiplexing time slices of transmission signals according to convergence time and convergence duration;

[0093] The module M1.4 includes: adopting the minimum mean square error criterion and setting the threshold of the minimum mean square error of the adaptive filter as a criterion for judging whether it has converged;

[0094] In time slicing, it is divided into a single-frequency sinusoidal signal, a transmission signal and a mark for distinguishing the single-frequency sinusoidal signal and the transmission signal. The duration of the single-frequency sinusoidal signal should be greater than or equal to the minimum mean square adaptive filter convergence time, and the duration of the transmission signal mark should be less than or equal to the time that the environment can make the minimum mean square adaptive filter converge.

[0095] The channel estimation module includes:

[0096] Module M2.1: adopts the minimum mean square adaptive filtering, takes the single-frequency sinusoidal signal time slice as the reference signal, takes the single-frequency sinusoidal signal received by the sink through the slowly varying complex environment as the input signal, and obtains the convergence coefficient of the minimum mean square adaptive filter;

[0097] Module M2.2: Calculate the noise power spectrum of the slowly varying complex environment at that moment according to the obtained tap coefficients of the least mean square adaptive filter.

[0098] The spectrum migration module includes:

[0099] Module M3.1: Determine the frequency band suitable for signal transmission according to the noise power spectrum, that is, the frequency band with lower noise spectrum amplitude, and inform the signal source;

[0100] Module M3.2: The signal source performs carrier modulation on the transmitted signal and moves the modulated signal to the frequency band;

[0101] The transmission signal identification steps include:

[0102] Module M4.1: The modulated signal is time-sliced ​​as a transmission signal and transmitted through a channel in a slowly varying complex environment, and received at the destination;

[0103] Module M4.2: Bandpass filter the measurement results according to the frequency of the transmission signal to obtain the signal and the narrowband interference with low amplitude, and perform window Fourier transform to obtain the spectrum. Use spectral subtraction to subtract the noise spectrum of the background noise in the corresponding time period to realize the identification of the transmission signal.

[0104] The embodiment of the present invention provides a communication method and system for signals in a slowly changing complex environment, which has a reasonable structure and is easy to use, and can overcome the defects of the prior art and realize communication under slowly changing non-steady-state background noise conditions; the present invention can realize adaptive spectrum shifting of transmission signals according to the measured interference spectrum, and realize interference suppression of communication channels in real time. The present invention has a wide range of applications, and the transmission signals include but are not limited to analog signals, coded signals, etc. The present invention has scalability and can be combined with coding technology and other means to further improve communication performance.

[0105] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0106] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A method for communicating signals in a slowly changing complex environment, characterized in that: include: Communication signal design steps: The signal source transmits a single-frequency sinusoidal signal through a channel in a slowly varying complex environment, which is received by the signal sink. According to the convergence of the tap coefficients of the least mean square adaptive filter, the single-frequency sinusoidal signal time slice used as a reference and the time division multiplexing time slice of the signal to be transmitted are designed; Channel estimation steps: The signal source transmits a single-frequency sinusoidal signal fragment, which is transmitted through the channel in a slowly varying complex environment. The signal sink receives the signal and uses the least mean square adaptive filter to obtain the tap coefficients that can converge to the environment. The noise power spectrum of the slowly varying complex environment is calculated. Spectrum shifting step: using the noise power spectrum to adjust the modulation frequency of the transmission signal, the signal source transmits the adjusted transmission signal, which is transmitted through a channel in a slowly varying complex environment and is received by the signal sink; The transmission signal identification step: performing spectrum analysis on the noise power spectrum and the modulation frequency to realize the identification of the transmission signal; Result step: Repeat the channel estimation step to the transmission signal identification step to achieve signal communication in a complex environment; The communication signal design step comprises: Step S1.1: Select a single-frequency sinusoidal signal, pass it through a slowly changing complex environment, and measure it after it is received at the destination to obtain the measured value at each moment; Step S1.2: Adopting the least mean square adaptive filtering, taking the single-frequency sinusoidal signal as the reference signal and the measured value as the input signal, and performing adaptive filtering; Step S1.3: by setting the error threshold, the convergence time and the convergence duration of the slowly changing complex environment are obtained; Step S1.4: designing the single-frequency sinusoidal signal time slice and the time division multiplexing time slice of the transmission signal according to the convergence time and the convergence duration; The step S1.4 comprises: adopting the minimum mean square error criterion and setting the threshold of the minimum mean square error of the adaptive filter as a criterion for judging whether the filter has converged; In the time slice, it is divided into a single-frequency sinusoidal signal, a transmission signal and a mark for distinguishing the single-frequency sinusoidal signal and the transmission signal, the duration of the single-frequency sinusoidal signal should be greater than or equal to the minimum mean square adaptive filter convergence time, and the duration of the mark of the transmission signal should be less than or equal to the time that the environment can make the minimum mean square adaptive filter converge; the channel estimation step includes: Step S2.1: adopting the least mean square adaptive filtering, taking the single-frequency sinusoidal signal time slice as the reference signal, taking the single-frequency sinusoidal signal received by the sink through the slowly varying complex environment as the input signal, and obtaining the convergence coefficient of the least mean square adaptive filter; Step S2.2: Calculate the noise power spectrum of the slowly varying complex environment at that moment according to the obtained tap coefficients of the least mean square adaptive filter.

2. The method for communicating signals in a slowly changing complex environment according to claim 1, characterized in that: The spectrum shifting step comprises: Step S3.1: determining a frequency band suitable for signal transmission according to the noise power spectrum, that is, a frequency band with a lower noise spectrum amplitude, and informing the signal source; Step S3.2: The information source performs carrier modulation on the transmitted signal and moves the modulated signal to the frequency band.

3. The method for communicating signals in a slowly changing complex environment according to claim 1, characterized in that: The transmission signal identification step comprises: Step S4.1: The modulated signal is time-sliced ​​as a transmission signal and transmitted via a channel in a slowly varying complex environment, and received at a destination; Step S4.2: Bandpass filter the measurement results according to the frequency of the transmission signal to obtain the signal and the narrowband interference with low amplitude, and perform window Fourier transform to obtain the spectrum. Use spectral subtraction to subtract the noise spectrum of the background noise in the corresponding time period to realize the identification of the transmission signal.

4. A communication system for signals in a slowly changing complex environment, characterized in that: include: Communication signal design module: Use a single-frequency sinusoidal signal to transmit through a channel in a slowly changing complex environment, receive it at the destination, and use the single-frequency sinusoidal signal time slice as a reference and the time division multiplexing time slice of the signal to be transmitted according to the convergence of the tap coefficients of the least mean square adaptive filter; Channel estimation module: using the single-frequency sinusoidal signal time slices, transmitting through the channel in a slowly varying complex environment, receiving at the destination, obtaining the tap coefficients that can converge to the environment through least mean square adaptive filtering, and calculating the noise power spectrum of the slowly varying complex environment based on this; Spectrum shifting module: uses the noise power spectrum to adjust the modulation frequency of the transmission signal, transmits it through a channel in a slowly changing complex environment, and receives it at the destination; Transmission signal identification module: performs spectrum analysis according to the noise power spectrum and modulation frequency to realize transmission signal identification; Result module: Repeat the channel estimation step to the transmission signal identification step to achieve signal communication in a complex environment; the communication signal design module includes: Module M1.1: Select a single-frequency sinusoidal signal, pass it through a slowly changing complex environment, and measure it after it is received by the destination to obtain the measured value at each moment; Module M1.2: adopting the least mean square adaptive filtering, taking the single-frequency sinusoidal signal as the reference signal and the measured value as the input signal, and performing adaptive filtering; Module M1.3: By setting the error threshold, the convergence time and convergence duration of the slowly changing complex environment are obtained; Module M1.4: Design single-frequency sinusoidal signal time slices and time-division multiplexing time slices of transmission signals according to convergence time and convergence duration; The module M1.4 includes: adopting the minimum mean square error criterion and setting the threshold of the minimum mean square error of the adaptive filter as a criterion for judging whether it has converged; In the time slice, it is divided into a single-frequency sinusoidal signal, a transmission signal and a mark for distinguishing the single-frequency sinusoidal signal and the transmission signal. The duration of the single-frequency sinusoidal signal should be greater than or equal to the minimum mean square adaptive filter convergence time, and the duration of the mark of the transmission signal should be less than or equal to the time when the environment can make the minimum mean square adaptive filter converge; the channel estimation module includes: Module M2.1: adopts the minimum mean square adaptive filtering, takes the single-frequency sinusoidal signal time slice as the reference signal, takes the single-frequency sinusoidal signal received by the sink through the slowly varying complex environment as the input signal, and obtains the convergence coefficient of the minimum mean square adaptive filter; Module M2.2: Calculate the noise power spectrum of the slowly varying complex environment at that moment according to the obtained tap coefficients of the least mean square adaptive filter.

5. The communication system for signals in a slowly changing complex environment according to claim 4, characterized in that: The spectrum shifting module includes: Module M3.1: Determine the frequency band suitable for signal transmission according to the noise power spectrum, that is, the frequency band with lower noise spectrum amplitude, and inform the signal source; Module M3.2: The signal source performs carrier modulation on the transmitted signal and moves the modulated signal to the frequency band; The transmission signal identification step comprises: Module M4.1: The modulated signal is time-sliced ​​as a transmission signal and transmitted through a channel in a slowly varying complex environment, and received at the destination; Module M4.2: Bandpass filter the measurement results according to the frequency of the transmission signal to obtain the signal and the narrowband interference with low amplitude, and perform window Fourier transform to obtain the spectrum. Use spectral subtraction to subtract the noise spectrum of the background noise in the corresponding time period to realize the identification of the transmission signal.

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