Maritime laser communication physical layer key negotiation encryption method and system

Abstract

The invention belongs to the technical field of laser communication, and particularly provides a maritime laser communication physical layer key negotiation encryption method and system. The method mainly comprises the following steps: acquiring a three-axis attitude angle time sequence of a first communication platform and a signal intensity time sequence of a laser detection signal synchronously received from a second communication platform to obtain a first signal intensity time sequence; and performing time alignment and filtering on the first signal intensity time sequence by taking the three-axis attitude angle time sequence as a time reference to obtain a second signal intensity time sequence. According to the invention, the two communication parties can consistently extract the random features modulated by the common physical shake from the observation data of the two communication parties, and completely consistent dependence on the instantaneous channel state is replaced, so that the generation success rate of the consistent key and the system reliability are remarkably improved in an offshore laser communication scene in which the platform continuously and independently shakes.

Description

Technical Field

[0001] This application belongs to the field of laser communication technology, and specifically relates to a physical layer key negotiation and encryption method and system for maritime laser communication. Background Technology

[0002] In the field of wireless communication security, physical layer key generation technology utilizes the physical characteristics of the channel to generate keys. A common method relies on the reciprocity of the channel. Under ideal conditions, the two communicating parties can measure highly similar channel responses in a short time by exchanging probe signals, enabling them to negotiate a consistent key from similar observations through subsequent processing.

[0003] However, in laser communication between small and medium-sized mobile platforms at sea, such as ships and buoys, the platforms are constantly swaying due to the influence of waves. This causes the communication link to have a rapidly changing dynamic multipath effect, which is formed by the relative motion of the platforms and complex reflection paths. However, because the swaying patterns and phases of the platforms are different, the channel states perceived by the transmitting and receiving parties at the same time are prone to significant differences. This leads to inconsistent random features extracted from this, a high key negotiation failure rate, and difficulty in the system working properly. Summary of the Invention

[0004] This application provides a physical layer key negotiation encryption method and system for maritime laser communication, which effectively solves the problem of high key negotiation failure rate caused by the destruction of instantaneous reciprocity of the channel due to the independent shaking of the maritime platform in the prior art. In the scenario of maritime laser communication with continuous independent shaking of the platform, it significantly improves the success rate of generating consistent keys and the reliability of the system.

[0005] To achieve the above objectives, this application adopts the following technical solution: In a first aspect, this application provides a method for encryption of physical layer key negotiation in maritime laser communication, comprising: acquiring a three-axis attitude angle time series of a first communication platform and a signal intensity time series of a laser detection signal synchronously received from a second communication platform to obtain a first signal intensity time series; using the three-axis attitude angle time series as a time reference, performing time alignment and filtering on the first signal intensity time series to obtain a second signal intensity time series; performing spectral analysis on the three-axis attitude angle time series and the second signal intensity time series respectively to obtain a three-axis attitude angle spectrum and a signal intensity spectrum; performing coherence analysis on the three-axis attitude angle spectrum and the signal intensity spectrum to obtain a coherent spectrum, extracting frequency components higher than a preset coherence threshold from the coherent spectrum to form a coherent frequency set; extracting amplitude and phase information from the frequency components indicated by the coherent frequency set from the signal intensity spectrum, and combining them to generate a sway feature vector; and generating a shared key based on the sway feature vector using a key derivation algorithm consistent with that of the second communication platform.

[0006] Secondly, this application provides a physical layer key negotiation and encryption system for maritime laser communication, comprising: Signal acquisition module: used to acquire the three-axis attitude angle time series of the first communication platform and the signal intensity time series of the laser detection signal synchronously received from the second communication platform to obtain the first signal intensity time series.

[0007] Signal preprocessing module: Used to perform time alignment and filtering on the first signal strength time series using the three-axis attitude angle time series as the time reference, to obtain the second signal strength time series.

[0008] Spectrum Analysis Module: Used to perform spectrum analysis on the three-axis attitude angle time series and the second signal intensity time series respectively, to obtain the three-axis attitude angle spectrum and the signal intensity spectrum.

[0009] Feature extraction module: used to perform coherence analysis on the three-axis attitude angle spectrum and signal intensity spectrum to obtain coherent spectrum, and extract frequency components above the preset coherence threshold from the coherent spectrum to form a coherent frequency set.

[0010] Feature generation module: used to extract amplitude and phase information from the frequency components indicated by the coherent frequency set from the signal intensity spectrum, and combine them to generate a sway feature vector.

[0011] Key generation module: Used to generate a shared key based on the shaking feature vector using a key derivation algorithm consistent with the second communication platform.

[0012] Thirdly, a readable storage medium includes: computer program instructions stored in the readable storage medium, which are read and executed by a processor to perform the steps of a physical layer key negotiation encryption method for maritime laser communication.

[0013] The beneficial effects of this application are: This application employs a scheme that combines analysis of the platform's own attitude swaying and the received signal fluctuation spectrum to screen out coherent frequency components dominated by relative swaying, and extracts signal amplitude and phase to construct feature vectors. This effectively solves the problem in existing technologies where independent swaying of the offshore platform disrupts the instantaneous reciprocity of the channel, leading to a high failure rate in key negotiation. It enables both communicating parties to consistently extract random features modulated by shared physical swaying from their own observation data, replacing the dependence on completely consistent instantaneous channel states. Thus, in offshore laser communication scenarios where the platform is continuously and independently swaying, the success rate of generating consistent keys and the reliability of the system are significantly improved.

[0014] Other features and advantages of this application will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures pointed out in the description and the accompanying drawings. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating the physical layer key negotiation encryption method for maritime laser communication according to this application is shown. Figure 2 A schematic diagram of the process for obtaining the coherent spectrum in this application is shown; Figure 3 A schematic diagram of the calculation process for the dynamic threshold in this application is shown; Figure 4 A schematic diagram of the process for generating sway feature vectors in this application is shown. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0018] This application utilizes the physical characteristics of relative motion generated by the two communicating platforms in a swaying marine environment, which are perceptible only to both parties, to generate a consistent random key, thereby solving the problem of channel reciprocity being destroyed and key negotiation failure rate being high due to independent platform swaying.

[0019] In some embodiments, such as Figure 1 As shown, this application provides a physical layer key negotiation encryption method for maritime laser communication, including: S1. Obtain the three-axis attitude angle time series of the first communication platform during the key negotiation period. The three-axis attitude angle time series is a set of data arranged in chronological order of the angle changes of the platform body relative to a certain reference coordinate system in the three rotational dimensions of roll, pitch, and heading. It contains the direct motion information of the platform's swaying caused by the sea waves.

[0020] Simultaneously, the first communication platform, through the photodetector of its laser communication terminal, synchronously receives a known laser signal emitted from the second communication platform for channel detection and measures the intensity of the signal, thereby obtaining a first signal intensity time series. This first signal intensity time series represents a record of the change in optical power of the laser detection signal reaching the receiver over time. Because laser transmission in atmospheric channels is affected by turbulence, scattering, and link alignment deviations and multipath effects caused by platform sway, the received intensity exhibits complex random fluctuations.

[0021] S2. Using a more accurate three-axis attitude angle time series as the time reference, the time of the signal strength data points is kept consistent with the time of the attitude angle data points. Then, the aligned signal strength data is filtered to remove high-frequency noise caused by circuit thermal noise, background light interference, etc., and retain low-frequency and in-band fluctuations caused by channel fading, thereby obtaining a cleaner second signal strength time series.

[0022] S3. Perform spectral analysis on the three-axis attitude angle time series and the second signal intensity time series respectively, converting the time-domain signals into their frequency-domain representations to obtain the three-axis attitude angle spectrum and the signal intensity spectrum. The three-axis attitude angle spectrum reflects the distribution of platform sway energy at different frequencies, with the main peak typically corresponding to the sway frequency caused by ocean waves. The signal intensity spectrum reflects the intensity of different frequency components in the received light intensity fluctuations.

[0023] S4. Perform coherence analysis on the three-axis attitude angle spectrum and the signal strength spectrum to obtain the coherent spectrum. The coherent spectrum contains multiple frequency points, each frequency point corresponds to an amplitude value, which is the coherence coefficient. Its value ranges from 0 to 1, representing the statistical similarity between the platform's own sway represented by the three-axis attitude angle time series and the received signal fluctuation represented by the second signal strength time series at that frequency point. The closer the value is to 1, the more likely the signal strength fluctuation at that frequency point is caused by the current platform's attitude sway.

[0024] Frequency components above a preset coherence threshold are extracted from the coherent spectrum to form a coherent frequency set. The coherent frequency set is considered to contain a set of frequencies that can be used for key generation and are dominated by the relative oscillation of the first and second communication platforms.

[0025] The coherence threshold is used to determine whether coherence is significant. A specific method for determining the coherence threshold is as follows: extract the amplitude values ​​of all frequency points in the coherent spectrum to form a coherent amplitude sequence, calculate the arithmetic mean and standard deviation of the coherent amplitude sequence, and use the sum of the arithmetic mean and standard deviation as the coherence threshold.

[0026] S5. Extract the amplitude and phase information from the frequency components indicated by the coherent frequency set from the signal intensity spectrum, combine them to generate a sway feature vector, thereby aggregating and quantizing the physical features scattered at different frequencies and related to relative sway, as the original entropy source for key generation.

[0027] S6. Based on the shaking feature vector, a shared key is generated using a key derivation algorithm consistent with the second communication platform.

[0028] For example, during the 10-second negotiation period, the inertial measurement unit of the first communication platform outputs attitude data 100 times per second, thereby obtaining a three-axis attitude angle time series with a length of 1,000 data points, recording the continuous changes in the ship's roll, pitch, and heading. At the same time, the photodetector of its laser communication terminal samples the detection laser from the second communication platform at the same frequency, obtaining a first signal intensity time series containing 1,000 intensity values.

[0029] The first communication platform uses a high-precision timescale of the three-axis attitude angle time series as a reference to interpolate and resample the first signal strength time series, ensuring precise alignment of the two time points. Subsequently, a low-pass filter with a cutoff frequency of 20Hz is used to filter the aligned strength data, removing circuit noise higher than 20Hz, to obtain the second signal strength time series.

[0030] The first communication platform performed a 1024-point Fast Fourier Transform on the three-axis attitude angle time series and the second signal intensity time series to obtain the three-axis attitude angle spectrum and the signal intensity spectrum. The analysis revealed that the three-axis attitude angle spectrum had two obvious spectral peaks at 0.2Hz and 0.5Hz, which is consistent with the main sway frequency of the current sea state; the signal intensity spectrum also showed a high spectral peak near the same frequency.

[0031] The first communication platform calculates the coherence between the three-axis attitude angle spectrum and the signal strength spectrum to obtain the coherent spectrum. Assuming that... At this point, the coherence coefficient is as high as ;exist At this point, the coherence coefficient is At 1.5 Hz, the coherence coefficient is only... The first communication platform calculates the average amplitude value of the entire coherent spectrum as follows: The standard deviation is Set the preset coherence threshold to , and The frequency points are preserved. The frequency points are filtered out, forming a coherent frequency set. .

[0032] The first communication platform extracts frequency from the signal strength spectrum. The amplitude at the point and phase and the amplitude at a frequency of 0.5Hz and phase Arrange these four values ​​in order Arranged to form a shaking feature vector .

[0033] The first communication platform inputs the shaking feature vector into the pre-agreed input from both parties. A hash function yields a The hash digest of the bits, then truncated. Bits, used as the shared key generated in this negotiation, are executed in exactly the same process locally on the second communication platform. Because the physical shaking it perceives is relative to that of the first communication platform, it can also extract a highly consistent shaking feature vector, ultimately generating the same... Bit-shared key.

[0034] In some embodiments, obtaining the three-axis attitude angle time series of the first communication platform includes: S11. Obtain the three-axis angular velocity time series and the three-axis acceleration time series of the first communication platform. The three-axis angular velocity time series records the change of the rotational angular velocity of the first communication platform around the three axes of its body coordinate system with time, reflecting the speed of the first communication platform's sway. The three-axis acceleration time series records the change of the linear acceleration of the platform along the three axes of its body coordinate system with time.

[0035] S12. Based on the three-axis angular velocity time series and the three-axis acceleration time series, the three-axis attitude angle time series is calculated using the complementary filter attitude solution algorithm.

[0036] In some embodiments, such as Figure 2 As shown, coherence analysis was performed on the three-axis attitude angle spectrum and signal intensity spectrum to obtain the coherent spectrum, including: S41. Extract the amplitude of each frequency point from the three-axis attitude angle spectrum and the signal intensity spectrum to obtain the attitude angle spectrum amplitude sequence and the signal intensity spectrum amplitude sequence; extract the phase information sequence from the three-axis attitude angle spectrum.

[0037] S42. The standard coherence spectrum is calculated based on the attitude angle spectrum amplitude sequence and the signal intensity spectrum amplitude sequence.

[0038] S43. Based on the attitude angle spectrum amplitude sequence, signal strength spectrum amplitude sequence, and phase information sequence, calculate the dynamic threshold, and filter out significant coherent frequency components with a coherent frequency coefficient greater than the dynamic threshold from the standard coherent spectrum. That is, retain the frequency points with a coherence coefficient higher than the corresponding dynamic threshold, and set the amplitude of the filtered frequency points to 0 to obtain the coherent spectrum. The coherent spectrum highlights the frequency components with a coherence significantly higher than the local noise level.

[0039] For example, the first communication platform extracts frequencies from the three-axis attitude angle spectrum. The amplitude at each frequency point is used to obtain the attitude angle spectrum amplitude sequence. Simultaneously, the phase at these frequency points is extracted to obtain the phase information sequence. Similarly, the signal strength spectrum amplitude sequence is extracted from the signal strength spectrum. The first communication platform uses the coherence formula to calculate the standard coherence spectrum of the attitude angle spectrum amplitude sequence and the signal strength spectrum amplitude sequence, and calculates the amplitude at each frequency point. At this point, the standard coherence coefficient The dynamic threshold is calculated. ;exist At this point, the standard coherence coefficient The dynamic threshold is ,but and The frequency point at that location is preserved, and the coherence coefficient is written into the new spectrum. If it exists... The coherence coefficient calculated at this location is less than The dynamic threshold at that point, The amplitude of the frequency point in the new spectrum is set to The final product is the coherent spectrum.

[0040] In some embodiments, such as Figure 3 As shown, the dynamic threshold is calculated based on the attitude angle spectrum amplitude sequence, the signal strength spectrum amplitude sequence, and the phase information sequence, including: S431. Calculate the energy proportion of each frequency point in the attitude angle spectrum amplitude sequence and the signal strength spectrum amplitude sequence respectively to obtain the first energy proportion and the second energy proportion. The first energy proportion is the proportion of the attitude angle spectrum energy at that frequency point to the total attitude angle spectrum energy in the coherent analysis band, and the second energy proportion is the proportion of the signal strength spectrum energy at that frequency point to the total signal strength spectrum energy in the coherent analysis band.

[0041] S432. Calculate the phase concentration index at each frequency point in the phase information sequence based on the first energy proportion and the second energy proportion. , , Represents the phase information sequence at frequency points The value, This represents the average value of the phase information sequence across all frequency points within a preset coherence analysis band. It measures the degree of deviation between the current frequency point's phase and the average phase; the smaller the deviation, the better. The closer the value is to 1, the more stable the phase.

[0042] The coherence analysis band is used to limit the range of energy percentage and phase average value calculation. One possible method for determining the coherence analysis band is as follows: obtain the energy value of each frequency point in the signal strength spectrum amplitude sequence and calculate the total energy; start accumulating the energy of each frequency point in the order of the frequency points to form a cumulative energy sequence, and calculate the energy value of all frequency points in the cumulative energy sequence to obtain the cumulative energy value. When the cumulative energy value first reaches or reaches 90% of the total energy, extract the frequency points with the minimum and maximum energy values ​​in the cumulative energy sequence set as the lower limit and upper limit of the band. The frequency range defined by the lower limit and upper limit is the coherence analysis band.

[0043] S433. Calculate the initial threshold for each frequency point based on the first energy proportion, the second energy proportion, and the phase concentration index. , ,in, Representing frequency point The dynamic threshold at that location This represents a preset baseline threshold constant. Represents the proportion of primary energy. This represents the second energy percentage. The initial threshold is mapped to the interval using a max-min normalization method. To obtain the dynamic threshold .

[0044] Reference threshold constant To adaptively reflect the overall energy distribution characteristics of the currently observed signal, one possible method for determining the reference threshold constant is: calculate the product sequence of the first energy proportion and the second energy proportion at all frequency points; calculate the geometric mean of the product sequence, and use the geometric mean as the reference threshold constant.

[0045] For example, the first communication platform analyzes the signal strength spectrum amplitude sequence and finds that most of the energy is concentrated in... arrive Between, from Start accumulating energy at each frequency point; when the accumulation reaches... When the accumulated energy reaches the total energy ,exist arrive Within this frequency range, find the frequency point with the minimum energy as the lower limit. The frequency point with the highest energy is used as the upper limit. This defines the coherence analysis frequency band. .

[0046] In frequency band Inside, the first communication platform calculates each frequency point. First energy percentage Second energy ratio At the same time, calculate the frequency band. Average value of the inner phase information sequence Then, the phase concentration index at each frequency point is calculated. ,for The frequency point at that point, , , The final calculation ,for The frequency point at that point, .

[0047] In some embodiments, such as Figure 4 As shown, amplitude and phase information are extracted from the frequency components indicated by the coherent frequency set from the signal intensity spectrum, and combined to generate a jitter feature vector, including: S51. Extract the amplitude value of each frequency point contained in the coherent frequency set from the signal intensity spectrum to form a first amplitude sequence; extract the phase value of each frequency point contained in the coherent frequency set from the signal intensity spectrum to form a first phase sequence.

[0048] S52. The first amplitude sequence and the first phase sequence may contain noise and phase jumps. Based on the first amplitude sequence and the first phase sequence, the data quality is improved by joint amplitude and phase enhancement to obtain the second amplitude sequence and the second phase sequence.

[0049] S53. Arrange the elements in the second amplitude sequence and the second phase sequence in order of frequency, and combine them to obtain the swaying feature vector.

[0050] For example, the first communication platform is based on a coherent frequency set Extract from the signal strength spectrum The amplitude at the point phase radian, The amplitude at the point phase radians constitute the first amplitude sequence and the first phase sequence The first communication platform performs joint enhancement processing on the first amplitude sequence and the first phase sequence to obtain the optimized second amplitude sequence. Second phase sequence The first communication platform concatenates the two sequences to obtain the shaking feature vector. .

[0051] In some embodiments, based on a first amplitude sequence and a first phase sequence, a second amplitude sequence and a second phase sequence are obtained through joint amplitude and phase enhancement, including: S521. Perform frequency domain smoothing filtering on the first amplitude sequence to suppress rapid random fluctuations in the amplitude sequence, resulting in a smoothed amplitude sequence; the values ​​of the first phase sequence are usually wrapped in... Within the interval, when the actual phase changes significantly, the calculated phase will jump. Phase expansion is performed on the first phase sequence, and a continuous phase sequence is obtained by detecting and compensating for the phase jump.

[0052] S522. Calculate the phase difference between adjacent frequency points in a continuous phase sequence. The second amplitude sequence is calculated based on the smoothed amplitude sequence and the phase difference. , , Represents a smoothed amplitude sequence. The amplitude is represented by the phase difference between adjacent frequency points in a continuous phase sequence. The amplitude is weighted by the stability of the phase change. The more drastic the phase change, the more the amplitude weight is suppressed. The more stable the phase, the more the amplitude weight is retained.

[0053] Mapping continuous phase sequences to standard phase principal value intervals This yields the second phase sequence.

[0054] For example, the first communication platform communicates with the first amplitude sequence. Smoothing is performed to obtain a smoothed amplitude sequence. For the first phase sequence Phase unrolling is performed, and the continuous phase sequence remains the same. The phase difference was calculated. radians, for The frequency point was calculated to obtain , continuous phase sequence Mapped to standard phase principal value range Since it is already within this interval, the second phase sequence is... .

[0055] In some embodiments, a shared key is generated based on the shaking feature vector using a key derivation algorithm consistent with the second communication platform, including: S61. Take the shaking feature vector as input and calculate it using a hash function, such as the SHA-256 algorithm. This function accepts input of arbitrary length and outputs a fixed-length, seemingly random bit string to obtain a hash digest.

[0056] S62. Extract a bit sequence of a specified length from the hash digest. For example, if a 128-bit key is required, extract from... Bit Extracting the first part of the abstract Bits, used as the final shared key.

[0057] For example, the first communication platform will shake the feature vector. Convert to byte stream, as The input to the hash function is used to calculate a result. Hash digest of bits: The first communication platform receives the hash digest from the previous Bits are extracted, for example ,Should The binary sequence of bits is the shared key generated in this negotiation. The second communication platform independently executes the same process to generate the same key.

[0058] In some embodiments, this application provides a physical layer key negotiation encryption system for maritime laser communication, comprising: Signal acquisition module: used to acquire the three-axis attitude angle time series of the first communication platform and the signal intensity time series of the laser detection signal synchronously received from the second communication platform to obtain the first signal intensity time series.

[0059] Signal preprocessing module: Used to perform time alignment and filtering on the first signal strength time series using the three-axis attitude angle time series as the time reference, to obtain the second signal strength time series.

[0060] Spectrum Analysis Module: Used to perform spectrum analysis on the three-axis attitude angle time series and the second signal intensity time series respectively, to obtain the three-axis attitude angle spectrum and the signal intensity spectrum.

[0061] Feature extraction module: used to perform coherence analysis on the three-axis attitude angle spectrum and signal intensity spectrum to obtain coherent spectrum, and extract frequency components above the preset coherence threshold from the coherent spectrum to form a coherent frequency set.

[0062] Feature generation module: used to extract amplitude and phase information from the frequency components indicated by the coherent frequency set from the signal intensity spectrum, and combine them to generate a sway feature vector.

[0063] Key generation module: Used to generate a shared key based on the shaking feature vector using a key derivation algorithm consistent with the second communication platform.

[0064] In some embodiments, this application provides a readable storage medium, including: computer program instructions stored in the readable storage medium, wherein the computer program instructions are read and executed by a processor to perform the steps of a digital marketing method.

[0065] It should be noted that, in this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0066] Any references to memory, storage, database, or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory.

[0067] Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A physical layer key negotiation and encryption method for maritime laser communication, characterized in that, include: The first signal intensity time series is obtained by acquiring the three-axis attitude angle time series of the first communication platform and the signal intensity time series of the laser detection signal synchronously received from the second communication platform. Using the triaxial attitude angle time series as a time reference, the first signal strength time series is time-aligned and filtered to obtain the second signal strength time series. Spectral analysis was performed on the three-axis attitude angle time series and the second signal intensity time series to obtain the three-axis attitude angle spectrum and the signal intensity spectrum. Coherence analysis is performed on the three-axis attitude angle spectrum and signal strength spectrum to obtain a coherent spectrum. Frequency components higher than a preset coherence threshold are extracted from the coherent spectrum to form a coherent frequency set. The amplitude and phase information of the frequency components indicated by the coherent frequency set are extracted from the signal intensity spectrum and combined to generate a sway feature vector; Based on the shaking feature vector, a shared key is generated using a key derivation algorithm consistent with that of the second communication platform.

2. The method according to claim 1, characterized in that, Obtain the three-axis attitude angle time series of the first communication platform, including: Obtain the three-axis angular velocity time series and three-axis acceleration time series of the first communication platform; Based on the aforementioned three-axis angular velocity time series and three-axis acceleration time series, the three-axis attitude angle time series is calculated using a complementary filter attitude solution algorithm.

3. The method according to claim 1, characterized in that, Perform coherence analysis on the three-axis attitude angle spectrum and signal strength spectrum to obtain the coherent spectrum, including: The amplitude of each frequency point is extracted from the three-axis attitude angle spectrum and the signal intensity spectrum to obtain the attitude angle spectrum amplitude sequence and the signal intensity spectrum amplitude sequence, respectively; the phase information sequence is extracted from the three-axis attitude angle spectrum. The standard coherence spectrum is calculated based on the attitude angle spectrum amplitude sequence and the signal intensity spectrum amplitude sequence. Based on the attitude angle spectrum amplitude sequence, signal intensity spectrum amplitude sequence, and phase information sequence, a dynamic threshold is calculated, and significant coherent frequency components greater than the dynamic threshold are selected from the standard coherent spectrum to obtain the coherent spectrum.

4. The method according to claim 3, characterized in that, Based on the attitude angle spectrum amplitude sequence, signal strength spectrum amplitude sequence, and phase information sequence, a dynamic threshold is calculated, including: Calculate the energy percentage of each frequency point in the attitude angle spectrum amplitude sequence and the signal strength spectrum amplitude sequence respectively to obtain the first energy percentage and the second energy percentage; Based on the first energy ratio and the second energy ratio, calculate the phase concentration index at each frequency point in the phase information sequence. , , This represents the average value of the phase information sequence across all frequency points within a preset coherence analysis band. Based on the first energy proportion, the second energy proportion, and the phase concentration index, calculate the initial threshold for each frequency point. , ,in, This represents a preset baseline threshold constant. Represents the proportion of primary energy. This represents the proportion of the second energy source; Map the initial threshold to an interval The dynamic threshold is obtained.

5. The method according to claim 1, characterized in that, The method for determining the coherence threshold is as follows: Extract the amplitude values ​​of all frequency points in the coherent spectrum to form a coherent amplitude sequence; Calculate the arithmetic mean and standard deviation of the coherent amplitude sequence, and use the sum of the arithmetic mean and standard deviation as the coherence threshold.

6. The method according to claim 4, characterized in that, The method for determining the reference threshold constant is as follows: Calculate the product sequence of the first energy percentage and the second energy percentage at all frequency points; Calculate the geometric mean of the product sequence and use the geometric mean as a benchmark threshold constant.

7. The method according to claim 1, characterized in that, The amplitude and phase information of the frequency components indicated by the coherent frequency set are extracted from the signal intensity spectrum and combined to generate a jitter feature vector, including: From the signal intensity spectrum, the amplitude value of each frequency point contained in the coherent frequency set is extracted to form a first amplitude sequence; from the signal intensity spectrum, the phase value of each frequency point contained in the coherent frequency set is extracted to form a first phase sequence. Based on the first amplitude sequence and the first phase sequence, a second amplitude sequence and a second phase sequence are obtained through joint enhancement of amplitude and phase. The elements in the second amplitude sequence and the second phase sequence are arranged in frequency order and combined to obtain the sway feature vector.

8. The method according to claim 7, characterized in that, Based on the first amplitude sequence and the first phase sequence, a second amplitude sequence and a second phase sequence are obtained through joint amplitude and phase enhancement, including: The first amplitude sequence is subjected to frequency domain smoothing filtering to obtain a smoothed amplitude sequence; the first phase sequence is subjected to phase expansion to obtain a continuous phase sequence. Calculate the phase difference between adjacent frequency points in a continuous phase sequence. The second amplitude sequence is calculated based on the smoothed amplitude sequence and the phase difference. , , Represents a smoothed amplitude sequence. Represents the phase difference between adjacent frequency points in a continuous phase sequence; maps the continuous phase sequence to a standard phase principal value range. This yields the second phase sequence.

9. The method according to claim 1, characterized in that, Based on the aforementioned wobbling feature vector, a shared key is generated using a key derivation algorithm consistent with the second communication platform, including: The shaking feature vector is used as input, and a hash digest is obtained by calculating it using a hash function; A bit sequence of a specified length is extracted from the hash digest and used as the final shared key.

10. A physical layer key negotiation and encryption system for maritime laser communication, characterized in that, include: Signal acquisition module: used to acquire the three-axis attitude angle time series of the first communication platform and the signal intensity time series of the laser detection signal synchronously received from the second communication platform to obtain the first signal intensity time series; Signal preprocessing module: used to perform time alignment and filtering on the first signal strength time series using the triaxial attitude angle time series as a time reference to obtain the second signal strength time series; Spectrum analysis module: used to perform spectrum analysis on the three-axis attitude angle time series and the second signal intensity time series respectively, to obtain the three-axis attitude angle spectrum and the signal intensity spectrum; Feature extraction module: used to perform coherence analysis on the three-axis attitude angle spectrum and signal intensity spectrum to obtain a coherent spectrum, and extract frequency components above a preset coherence threshold from the coherent spectrum to form a coherent frequency set; Feature generation module: used to extract amplitude and phase information from the frequency components indicated by the coherent frequency set from the signal intensity spectrum, and combine them to generate a sway feature vector; Key generation module: used to generate a shared key based on the shaking feature vector using a key derivation algorithm consistent with the second communication platform.

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