A bionic covert underwater acoustic communication and detection integrated method

Abstract

The application discloses a kind of bionic concealed underwater acoustic communication detection integrated method.Existing method does not consider the concealment of communication and detection jointly.The method of the present application first extracts click sound signal and whistle signal, and carries out power and correlation screening;Then the original click sound signal is waveform encoded and pulse position modulated, and the original whistle signal is time-frequency shape encoded and waveform parameter modulated.Using the good detection performance of bionic modulated signal, generate bionic communication detection integrated signal.In echo signal receiving end, different echo signal processing method is used.In communication receiving end, combined demodulation method is used.The bionic whistle signal generated by the present application has high similarity with the original signal in time domain, and the time-frequency profile is continuous.The present application can improve the communication rate by sampling combined modulation, has good concealment, not only can realize the accurate estimation of target distance, speed and azimuth, but also has good communication performance.

Description

Technical Field

[0001] This invention relates to the field of integrated underwater acoustic communication and target detection technology, and in particular to a biomimetic, covert underwater acoustic communication and detection integrated method. Background Technology

[0002] Modern military and civilian platforms need to simultaneously perform communication and detection functions. Traditional discrete designs increase system size, power consumption, and cost, while also reducing system compatibility. An integrated communication and detection design allows the communication and detection modules to share hardware resources, thus solving these problems.

[0003] To prevent underwater acoustic communication signals used for military purposes from being identified and deciphered during transmission, communication must be conducted covertly. Unlike traditional methods that reduce transmission power or increase modulation bandwidth, biomimetic covert underwater acoustic communication mimics the sounds of cetaceans, inducing non-communication partners to confuse the cetacean sounds with the biomimetic communication signal, thus eliminating the received signal and achieving concealment. Since biomimetic communication signals do not require reduced transmission energy, biomimetic covert underwater acoustic communication can achieve better transmission distance and bit error rate performance than existing covert underwater communication methods. Active sonar, in order to detect long-range targets in noisy underwater environments, needs to emit high-power detection signals to obtain the required signal-to-noise ratio. Therefore, active sonar also has security and covertness requirements. Considering both the covertness of underwater acoustic communication and the covertness of underwater acoustic detection is of great significance for applications such as underwater combat platforms.

[0004] Existing biomimetic covert communication methods, such as Chinese invention patent application number 202110111520.X, disclose a whale-eye whistle communication method based on segmented time-frequency profile delay modulation. This method modulates the whistle signal in segments, but its limitation lies in the discontinuity of the time-frequency profile of the generated biomimetic whistle signal, affecting its biomimetic camouflage performance. Existing integrated underwater communication and detection methods, such as Chinese invention patent application number 201910909461.3, disclose an integrated underwater communication and detection method. This method modulates communication information into the delay difference between adjacent pattern codes, using a generalized sinusoidal frequency-modulated signal as the pattern code. While achieving communication, it can estimate the target's distance and speed, but it does not consider estimating the target's orientation.

[0005] In summary, currently published patents do not include a method for integrating biomimetic covert underwater acoustic communication and detection. Biomimetic covert underwater acoustic communication methods need to address the trade-off between communication speed and covertness, aiming to improve communication speed without compromising covertness. Integrated underwater communication and detection methods require improved accuracy in estimating target location. Summary of the Invention

[0006] This invention addresses the stealth issues inherent in both underwater acoustic communication and active target detection by designing a biomimetic, stealthy, integrated method for underwater acoustic communication and target detection, achieving high-speed underwater acoustic communication and target detection.

[0007] The method of this invention is specifically as follows:

[0008] Step (1) Extract the original call signal: Use the frequency band variance endpoint detection method to extract the original ticking signal; use the dual threshold endpoint detection method to extract the original whistle signal.

[0009] Step (2) Based on power and correlation, filter the original ticking and whistle signals: retain the original ticking and whistle signals that are greater than the set power threshold and greater than the autocorrelation threshold and less than the cross-correlation threshold.

[0010] Step (3) involves combining and encoding the selected raw tick and whistle signals, as follows:

[0011] (3-1) The selected raw ticking signals are waveform encoded, and 2 N1 A ticking sound and 2 N1 The N1-bit binary information forms an encoding mapping relationship, that is, each original ticking signal carries N1 bits of information, thus completing the carrying of N1 bits of information;

[0012] (3-2) Pulse position modulation is applied to the selected original tick signals, and the modulation information is modulated onto the pulse time difference between adjacent original tick signals. The modulation information q is then modulated with 2 N2 The N2-bit binary information forms an encoding mapping relationship to complete the carrying of the N2-bit information; where the time difference between the i-th and i+1-th original ticks is... Modulation information q = 1, 2, ..., 2 N2 T c The maximum time interval between adjacent ticks in each tick combination, i.e., the modulation duration, T. c Occupy 2 N2 The minimum time difference, i.e., the modulation interval There are 2 N2 A possible pulse time difference.

[0013] (3-3) Using the selected original whistle signals as prototypes, a biomimetic whistle signal is constructed, and waveform parameter modulation is applied to the biomimetic whistle signal: The time-domain envelope of the selected original whistle signals is used to modulate the envelopes of the single-frequency signal and the linear frequency modulated signal, and then waveform parameter modulation is performed to generate the modulated biomimetic whistle signal, represented as follows: A l(t) represents the time-domain envelope of the l-th harmonic at time t in the original whistle signal, where l = 1, 2, ..., L, and L is the number of harmonics. c The center frequency of the original whistle signal, frequency modulation. δ B The modulation interval is the bandwidth. The modulation interval is the duration. k = 0 indicates modulation of a single-frequency signal, k ≠ 0 indicates modulation of a linear frequency modulated signal, b and d are the modulation information carried by the modulated signal of the bionic whistle, and the combination scheme of b and d is the same as 2. N3 The N3-bit binary information forms an encoding mapping relationship, thus completing the carrying of the N3-bit information.

[0014] (3-4) Encode the time-frequency shape of the bionic whistle modulated signal, the time-frequency shape being similar to 2... N4 The N4-bit binary information forms an encoding mapping relationship, thus completing the carrying of the N4-bit information.

[0015] Step (4) generates a bionic communication and detection integrated signal, which consists of the original ticking sound synchronization signal, the ticking sound detection signal, the ticking sound modulated signal, the bionic whistle sound detection signal, and the bionic whistle sound modulated signal; among them, the synchronization signal is used for frame synchronization of the signal, the ticking sound detection signal and the bionic whistle sound detection signal are used for target detection, and the ticking sound modulated signal and the bionic whistle sound modulated signal are used for communication.

[0016] Step (5) Active Target Detection: The receiver of the target detection receives the integrated communication and detection signal, processes the ticking detection signal using the time-delay ranging method to obtain an estimate of the target distance, and processes the bionic whistle detection signal using the Doppler velocity measurement method and the array direction finding method to obtain estimates of the target velocity and azimuth information, respectively. Specifically, as follows:

[0017] (5-1) Using the ambiguity function, the propagation time difference between the transmitted signal and the received echo signal is estimated to estimate the target distance: The ambiguity function χ(τ,κ) is the correlation function between the tick detection signal u(t) and its echo signal u(κ(t-τ)) in the integrated biomimetic communication detection signal transmission. Where κ is the Doppler factor, τ is the time delay corresponding to the peak value of the ambiguity function of the tick detection signal, and the superscript * indicates conjugate; the distance estimate between the detected target and the echo signal receiver is... c is the underwater equivalent speed of sound.

[0018] (5-2) The fractional Fourier transform is used to estimate the Doppler factor and thus estimate the target's velocity.

[0019] A fractional Fourier transform is performed on the biomimetic whistle detection signal. In the optimal Fourier domain, the energy of the biomimetic whistle detection signal is concentrated, producing a peak. At this point, the angle between the optimal Fourier domain and the time axis is the optimal rotation angle.

[0020] Optimal rotation angle using fractional Fourier transform Relationship with the frequency k of the modulated signal of the bionic whistle Obtain an estimate of the frequency modulation of the echo signal. Among them, time resolution Frequency resolution N is the number of sampling points, f s The sampling frequency.

[0021] The Doppler factor estimate is obtained by utilizing the relationship between the Doppler factor and the frequency modulation rate. This allows us to obtain an estimate of the target's moving speed.

[0022] (5-3) The target azimuth is estimated using an M-element uniformly distributed linear array, specifically:

[0023] Array output signal Among them, v p (t) is the whistle detection echo signal in the p-th biomimetic communication and detection integrated signal at time t, where p = 1, 2, ..., P, and P is the number of whistle detection echo signals; D is the element spacing, θ p n is the incident azimuth angle of the whistle detection echo signal in the p-th biomimetic communication and detection integrated signal relative to the array. m (t) represents the noise at the m-th element, m = 1, 2, ..., M, where M is the number of elements in the array. The array output covariance matrix B = E[x(t)x H (t)], E[·] represents the mean operation, and the superscript H represents transpose and conjugate;

[0024] For each array element, the target azimuth angle is estimated using the incoherent signal subspace method: the bandwidth of the broadband signal is divided into J sub-bands, and for the center frequency f... j The subband covariance matrix B(f) j Perform eigenvalue decomposition, B(f) j )=U(f j )Λ(f j )U(f j ) H , j = 1, 2, ..., J; where, the eigenvector U(f j )=[U S (fj )U N (f j )], eigenvalues U S (f j ) represents the signal feature vector, U N (f j ) represents the noise feature vector, Λ S (f j ) represents the signal characteristic value, Λ N (f j ) represents the noise characteristic value;

[0025] When the direction vector a(f) j When the Euclidean distance between (θ) and the signal subspace is minimized, a high spectral peak is obtained at the azimuth angle θ; using the spatial spectrum of each sub-band Obtain the broadband spatial spectrum An angular scan of the broadband spatial spectrum is performed to find the peak position of the spatial spectrum. The incident angle of the signal corresponding to the peak is the estimated value of the target azimuth angle.

[0026] Step (6) The receiving end of the communication receives the integrated communication detection signal and performs combined demodulation and decoding of the biomimetic modulated signal:

[0027] The transmitter and receiver share a sound signal database, and the i′-th received bionic modulated signal r i′ (t) and the j′th local signal c in the vocalization signal database j′ The cross-correlation function of (t) is expressed as: τ′ represents the time delay corresponding to the correlation peak; by using the local signal number j′ corresponding to the correlation peak and performing an inverse mapping with the binary sequence, the decoded sequence is obtained. Specifically:

[0028] (6-1) Calculated using the modulated signal of the ticking sound and the local signal of the ticking sound. N1 By analyzing the cross-correlation function values, the location of the correlation peak is obtained, and the local signal number of the tick is estimated. Then, the N1-bit information is decoded using the inverse mapping between the local signal number and the binary sequence.

[0029] (6-2) Using the position t of the correlation peak of the adjacent x-th and x′=x+1-th tick modulated signals x and t x′ And the corresponding pulse width T of the modulated signal x and T x′ The time delay difference between the two ticking modulated signals is obtained. Using pulse position expression The q value is obtained, and the N2-bit information is demodulated by using the inverse mapping between q and the binary sequence.

[0030] (6-3) Short-time Fourier transform is used to perform time-frequency shape analysis to determine the local whistle signal corresponding to the time-frequency shape; the N4-bit information of the bionic whistle modulated signal is decoded by using the inverse mapping between the time-frequency shape and the binary sequence.

[0031] (6-4) Calculate the 2 using the whistle local signal and the bionic whistle modulated signal determined in (6-3). N3 The local signal number of the whistle is estimated using the cross-correlation function values; the N3-bit modulation information is demodulated using the inverse mapping between the local signal number of the whistle and the binary sequence.

[0032] The present invention has the following beneficial effects:

[0033] (1) This invention takes into account the overall original whistle signal structure characteristics, rather than simply dividing the whistle signal in the time domain. On the one hand, it can enable the modulated whistle signal to carry more energy and reduce the bit error rate of communication. On the other hand, it is also to improve biomimicry. Without segmenting the whistle signal, the time-frequency profile of the signal can be smoother and more continuous.

[0034] (2) This invention addresses the problem of low communication rates in current biomimetic covert communication methods by fully utilizing the signal structure of the original call signal, namely the combination of a ticking sound and a whistle. The original ticking sound signal and the biomimetic whistle signal are modulated together. This improves the communication rate, and using the original ticking sound signal further enhances the covertness of the communication signal.

[0035] (3) Based on the excellent detection performance of the call signal and considering the concealment issue of active sonar, this invention proposes an integrated biomimetic concealed underwater acoustic communication and detection method based on the signal design of the biomimetic concealed underwater acoustic communication method. The original ticking signal is used as the distance detection signal, and the biomimetic whistle modulated signal is used as the velocity and azimuth detection signal. This achieves accurate estimation of the target's distance, velocity, and azimuth while maintaining the communication performance of the biomimetic communication method. Attached Figure Description

[0036] Figure 1 This is a flowchart of the method of the present invention;

[0037] Figure 2 A schematic diagram of pulse position modulation when modulation information q = 1, 2, 3, 4;

[0038] Figure 3 A schematic diagram of the biomimetic whistle signal being tuned;

[0039] Figure 4 A schematic diagram of the integrated signal frame structure for biomimetic communication and detection. Detailed Implementation

[0040] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0041] A biomimetic, covert underwater acoustic communication and detection integrated method, the specific process of which is as follows: Figure 1 As shown.

[0042] Step (1) Extract the original call signal: Use the frequency band variance endpoint detection method to extract the original ticking signal; use the dual threshold endpoint detection method to extract the original whistle signal.

[0043] Step (2) Based on power and correlation, filter the original ticking and whistle signals: retain the original ticking and whistle signals that are greater than the set power threshold and greater than the autocorrelation threshold and less than the cross-correlation threshold.

[0044] In this embodiment, the power threshold of the original tick signal is 0.1, and the power threshold of the original whistle signal is 0.6. The autocorrelation threshold of the original tick signal is 0.7, and the cross-correlation threshold is 0.3; the autocorrelation threshold of the original whistle signal is 0.7, and the cross-correlation threshold is 0.1.

[0045] Step (3) involves combining and encoding the selected raw tick and whistle signals, as follows:

[0046] (3-1) The selected raw ticking signals are waveform encoded, and 2 N1 A ticking sound and 2 N1 The N1-bit binary information forms an encoding mapping relationship, that is, each original ticking signal carries N1 bits of information, thus completing the carrying of N1 bits of information;

[0047] In this embodiment, the ticking sound database contains 128 high-quality ticking sounds, and N1 = 7.

[0048] (3-2) Pulse position modulation is applied to the selected original tick signals, and the modulation information is modulated onto the pulse time difference between adjacent original tick signals. The modulation information q is then modulated with 2 N2 The N2-bit binary information forms an encoding mapping relationship to complete the carrying of the N2-bit information; where the time difference between the i-th and i+1-th original ticks is... Modulation information q = 1, 2, ..., 2 N2 T c The maximum time interval between adjacent ticks in each tick combination, i.e., the modulation duration, T. c Occupy 2 N2 The minimum time difference, i.e., the modulation interval There are 2 N2 A possible pulse time difference.

[0049] The specific modulation principle is as follows: Figure 2 As shown. In this embodiment, T c =200ms Rounding down gives 153, N2 = 7.

[0050] (3-3) Using the selected original whistle signals as prototypes, a biomimetic whistle signal is constructed, and waveform parameter modulation is applied to the biomimetic whistle signal: The time-domain envelope of the selected original whistle signals is used to modulate the envelopes of the single-frequency signal and the linear frequency modulated signal, and then waveform parameter modulation is performed to generate the modulated biomimetic whistle signal, represented as follows: A l (t) represents the time-domain envelope of the l-th harmonic at time t in the original whistle signal, where l = 1, 2, ..., L, and L is the number of harmonics. c The center frequency of the original whistle signal, frequency modulation. δ B The modulation interval is the bandwidth. The modulation interval is the duration. k = 0 indicates modulation of a single-frequency signal, k ≠ 0 indicates modulation of a linear frequency modulated signal, b and d are the modulation information carried by the modulated signal of the bionic whistle, and the combination scheme of b and d is the same as 2. N3 The N3-bit binary information forms an encoding mapping relationship, thus completing the carrying of the N3-bit information.

[0051] like Figure 3 As shown, in this embodiment, the maximum duration of the whistle signal is 500ms. When the duration is 50ms, there are 10 (500ms / 50ms) possible signal durations (i.e., the number of possible values ​​for b is 10). The maximum bandwidth of the whistle signal is 4kHz, δ B When the frequency is 200Hz, there are 20 (4000Hz / 200Hz) signal bandwidth schemes (i.e., the number of possible values ​​for d is 20). There are a total of b×d=200 combinations, N³=7, L=3, f c =1.5kHz.

[0052] (3-4) Encode the time-frequency shape of the bionic whistle modulated signal, the time-frequency shape being similar to 2... N4 The N4-bit binary information forms an encoding mapping relationship, thus completing the carrying of the N4-bit information.

[0053] In this embodiment, the time-frequency shape of the generated bionic whistle has three types: fixed frequency, up-sweep, and down-sweep. Therefore, N4 = 2.

[0054] Step (4) generates a bionic communication and detection integrated signal, which consists of the original ticking sound synchronization signal, the ticking sound detection signal, the ticking sound modulated signal, the bionic whistle sound detection signal, and the bionic whistle sound modulated signal; among them, the synchronization signal is used for frame synchronization of the signal, the ticking sound detection signal and the bionic whistle sound detection signal are used for target detection, and the ticking sound modulated signal and the bionic whistle sound modulated signal are used for communication.

[0055] A schematic diagram of the integrated signal frame structure for biomimetic communication and detection, as shown below. Figure 4 As shown.

[0056] Step (5) Active Target Detection: The receiver of the target detection receives the integrated communication and detection signal, processes the ticking detection signal using the time-delay ranging method to obtain an estimate of the target distance, and processes the bionic whistle detection signal using the Doppler velocity measurement method and the array direction finding method to obtain estimates of the target velocity and azimuth information, respectively. Specifically, as follows:

[0057] (5-1) Using the ambiguity function, the propagation time difference between the transmitted signal and the received echo signal is estimated to estimate the target distance: The ambiguity function χ(τ,κ) is the correlation function between the tick detection signal u(t) and its echo signal u(κ(t-τ)) in the integrated biomimetic communication detection signal transmission. Where κ is the Doppler factor, τ is the time delay corresponding to the peak value of the ambiguity function of the tick detection signal, and the superscript * indicates conjugate; the distance estimate between the detected target and the echo signal receiver is... c is the underwater equivalent speed of sound.

[0058] In this embodiment, the duration of the ticking detection signal u(t) is 0.02s, the bandwidth is 5kHz, c is 1500m / s, κ is 0.99, and τ is 2.7s.

[0059] (5-2) The fractional Fourier transform is used to estimate the Doppler factor and thus estimate the target's velocity.

[0060] A fractional Fourier transform is performed on the biomimetic whistle detection signal. In the optimal Fourier domain, the energy of the biomimetic whistle detection signal is concentrated, producing a peak. At this point, the angle between the optimal Fourier domain and the time axis is the optimal rotation angle.

[0061] Optimal rotation angle using fractional Fourier transform Relationship with the frequency k of the modulated signal of the bionic whistle Obtain an estimate of the frequency modulation of the echo signal. Among them, time resolution Frequency resolution N is the number of sampling points, f s The sampling frequency.

[0062] The Doppler factor estimate is obtained by utilizing the relationship between the Doppler factor and the frequency modulation rate. This allows us to obtain an estimate of the target's moving speed.

[0063] In this embodiment, the duration of the bionic whistle detection signal is 0.1s, the bandwidth is 1kHz, the center frequency is 1.5kHz, and f s =44100Hz, N=f s / Δf=4410, Δf is 10Hz, k=10000,

[0064] (5-3) The target azimuth is estimated using an M-element uniformly distributed linear array, specifically:

[0065] Array output signal Among them, v p (t) is the whistle detection echo signal in the p-th biomimetic communication and detection integrated signal at time t, where p = 1, 2, ..., P, and P is the number of whistle detection echo signals; D is the element spacing, θ p n is the incident azimuth angle of the whistle detection echo signal in the p-th biomimetic communication and detection integrated signal relative to the array. m (t) represents the noise at the m-th element, m = 1, 2, ..., M, where M is the number of elements in the array. The array output covariance matrix B = E[x(t)x H (t)], E[·] represents the mean operation, and the superscript H represents transpose and conjugate;

[0066] For each array element, the target azimuth angle is estimated using the incoherent signal subspace method: the bandwidth of the broadband signal is divided into J sub-bands, and for the center frequency f... j The subband covariance matrix B(f) j Perform eigenvalue decomposition, B(f) j )=U(f j )Λ(f j )U(f j ) H , j = 1, 2, ..., J; where, the eigenvector U(f j )=[U S (f j )U N (f j )], eigenvalues U S (f j) represents the signal feature vector, U N (f j ) represents the noise feature vector, Λ S (f j ) represents the signal characteristic value, Λ N (f j ) represents the noise characteristic value;

[0067] When the direction vector a(f) j When the Euclidean distance between (θ) and the signal subspace is minimized, a high spectral peak is obtained at the azimuth angle θ; using the spatial spectrum of each sub-band Obtain the broadband spatial spectrum An angular scan of the broadband spatial spectrum is performed to find the peak position of the spatial spectrum. The incident angle of the signal corresponding to the peak is the estimated value of the target azimuth angle.

[0068] In this embodiment, the duration of the bionic whistle detection signal is 0.1s, the bandwidth is 1kHz, the center frequency is 1.5kHz, and there is one whistle detection echo signal, i.e., P=1, D=0.5, M=8, J=5, and the maximum value of P(θ) is 3.4452, corresponding to the estimated angle value.

[0069] Step (6) The receiving end of the communication receives the integrated communication detection signal and performs combined demodulation and decoding of the biomimetic modulated signal:

[0070] The transmitter and receiver share a sound signal database, and the i′-th received bionic modulated signal r i′ (t) and the j′th local signal c in the vocalization signal database j′ The cross-correlation function of (t) is expressed as: τ′ represents the time delay corresponding to the correlation peak; by using the local signal number j′ corresponding to the correlation peak and performing an inverse mapping with the binary sequence, the decoded sequence is obtained. Specifically:

[0071] (6-1) Calculated using the modulated signal of the ticking sound and the local signal of the ticking sound. N1 By analyzing the cross-correlation function values, the location of the correlation peak is obtained, and the local signal number of the tick is estimated. Then, the N1-bit information is decoded using the inverse mapping between the local signal number and the binary sequence.

[0072] In this embodiment, the local ticking signal numbered 0 corresponds to bit information 0000000 for N1, and so on.

[0073] (6-2) Using the position t of the correlation peak of the adjacent x-th and x′=x+1-th tick modulated signals x and t x′And the corresponding pulse width T of the modulated signal x and T x′ The time delay difference between the two ticking modulated signals is obtained. Using pulse position expression The q value is obtained, and the N2-bit information is demodulated by using the inverse mapping between q and the binary sequence.

[0074] In this embodiment ΔT xx′ =10ms, q=8, the bit information corresponding to N2 is 0001000.

[0075] (6-3) Short-time Fourier transform is used to perform time-frequency shape analysis to determine the local whistle signal corresponding to the time-frequency shape; the N4-bit information of the bionic whistle modulated signal is decoded by using the inverse mapping between the time-frequency shape and the binary sequence.

[0076] In this embodiment, for the fixed-frequency whistle signal, the bit information corresponding to N4 is 00; for the up-sweep whistle signal, the bit information corresponding to N4 is 01; and for the down-sweep whistle signal, the bit information corresponding to N4 is 11.

[0077] (6-4) Calculate the 2 using the whistle local signal and the bionic whistle modulated signal determined in (6-3). N3 The local signal number of the whistle is estimated using the cross-correlation function values; the N3-bit modulation information is demodulated using the inverse mapping between the local signal number of the whistle and the binary sequence.

[0078] In this embodiment, the local whistle signal numbered 0 has a bit information corresponding to N3 of 0000000, and so on.

[0079] The above embodiments are merely examples of implementations of the present invention. The scope of protection of the present invention should not be limited to the specific forms described in the embodiments, and the scope of protection of the present invention should also include similar inventive methods conceived based on the present invention.

Claims

1. A biomimetic, covert underwater acoustic communication and detection integrated method, characterized in that, The method is as follows: Step (1) Extract the original call signal: Use the frequency band variance endpoint detection method to extract the original ticking signal; use the dual threshold endpoint detection method to extract the original whistle signal; Step (2) Based on power and correlation, filter the original tick and whistle signals: retain the original tick and whistle signals that are greater than the set power threshold and greater than the autocorrelation threshold and less than the cross-correlation threshold; Step (3) Combine the selected original ticking signal and whistle signal for information encoding and modulation. After encoding and modulation, each original ticking signal carries N1 and N2 bits of information, and each bionic whistle modulated signal carries N3 and N4 bits of information. Step (4) generates a biomimetic communication and detection integrated signal, which consists of the original ticking sound synchronization signal, the ticking sound detection signal, the ticking sound modulated signal, the biomimetic whistle sound detection signal, and the biomimetic whistle sound modulated signal; among them, the synchronization signal is used for frame synchronization of the signal, the ticking sound detection signal and the biomimetic whistle sound detection signal are used for target detection, and the ticking sound modulated signal and the biomimetic whistle sound modulated signal are used for communication; Step (5) Active target detection: The receiver of the target detection receives the integrated communication and detection signal, processes the ticking sound detection signal using the time delay ranging method, and obtains an estimate of the target distance; The biomimetic whistle detection signal was processed using the Doppler velocity measurement method and the array direction finding method to obtain estimates of the target velocity and azimuth information, respectively. Step (6) The receiving end of the communication receives the integrated communication detection signal and performs combined demodulation and decoding of the biomimetic modulated signal: The transmitter and receiver share a sound signal database, and the i′-th received bionic modulated signal r i′ (t) and the j′th local signal c in the vocalization signal database j′ The cross-correlation function of (t) is expressed as: τ′ represents the time delay corresponding to the correlation peak; the local signal number j′ corresponding to the correlation peak is used to perform an inverse mapping with the binary sequence to obtain the decoded sequence.

2. The biomimetic covert underwater acoustic communication and detection integrated method as described in claim 1, characterized in that, The specific process of step (3) is as follows: (3-1) Waveform coding is performed on the original click sound signals screened out, 2 N1 click sounds and 2 N1 group N1-bit binary bit information constitute an encoding mapping relationship, that is, each original click sound signal carries N1-bit bit information, completing the carrying of N1-bit bit information; (3-2) Pulse position modulation is applied to the selected original tick signals, and the modulation information is modulated onto the pulse time difference between adjacent original tick signals. The modulation information q is then modulated with 2 N2 The N2-bit binary information forms an encoding mapping relationship to complete the carrying of the N2-bit information; where the time difference between the i-th and i+1-th original ticks is... Modulation information q = 1, 2, ..., 2 N2 T c The maximum time interval between adjacent ticks in each tick combination, i.e., the modulation duration, T. c Occupy 2 N2 The minimum time difference, i.e., the modulation interval There are 2 N2 Possible pulse time differences; (3-3) Using the selected original whistle signals as prototypes, a biomimetic whistle signal is constructed, and waveform parameter modulation is applied to the biomimetic whistle signal: The time-domain envelope of the selected original whistle signals is used to modulate the envelopes of the single-frequency signal and the linear frequency modulated signal, and then waveform parameter modulation is performed to generate the modulated biomimetic whistle signal, represented as follows: A l (t) represents the time-domain envelope of the l-th harmonic at time t in the original whistle signal, where l = 1, 2, ..., L, and L is the number of harmonics. c The center frequency of the original whistle signal, frequency modulation. δ B The modulation interval is the bandwidth. The modulation interval is the duration. k = 0 indicates modulation of a single-frequency signal, k ≠ 0 indicates modulation of a linear frequency modulated signal, b and d are the modulation information carried by the modulated signal of the bionic whistle, and the combination scheme of b and d is the same as 2. N3 The N3-bit binary information forms an encoding mapping relationship to complete the carrying of the N3-bit information; (3-4) Encode the time-frequency shape of the bionic whistle modulated signal, the time-frequency shape being similar to 2... N4 The N4-bit binary information forms an encoding mapping relationship, thus completing the carrying of the N4-bit information.

3. The biomimetic covert underwater acoustic communication and detection integrated method as described in claim 2, characterized in that, The specific process of step (5) is as follows: (5-1) Using the ambiguity function, the propagation time difference between the transmitted signal and the received echo signal is estimated to estimate the target distance: The ambiguity function χ(τ,κ) is the correlation function between the tick detection signal u(t) and its echo signal u(κ(t-τ)) in the integrated biomimetic communication detection signal transmission. Where κ is the Doppler factor, τ is the time delay corresponding to the peak value of the ambiguity function of the tick detection signal, and the superscript * indicates conjugate; the distance estimate between the detected target and the echo signal receiver is... c is the underwater equivalent speed of sound; (5-2) The fractional Fourier transform is used to estimate the Doppler factor and thus estimate the target's velocity. A fractional Fourier transform is performed on the biomimetic whistle detection signal. In the optimal Fourier domain, the energy of the biomimetic whistle detection signal is concentrated, producing a peak. At this point, the angle between the optimal Fourier domain and the time axis is the optimal rotation angle. Optimal rotation angle using fractional Fourier transform Relationship with the frequency k of the modulated signal of the bionic whistle Obtain an estimate of the frequency modulation of the echo signal. Among them, time resolution Frequency resolution N is the number of sampling points, f s The sampling frequency; The Doppler factor estimate is obtained by utilizing the relationship between the Doppler factor and the frequency modulation rate. This allows us to obtain an estimate of the target's moving speed. (5-3) The target azimuth is estimated using an M-element uniformly distributed linear array, specifically: Array output signal Among them, v p (t) is the whistle detection echo signal in the p-th biomimetic communication and detection integrated signal at time t, where p = 1, 2, ..., P, and P is the number of whistle detection echo signals; D is the element spacing, θ p n is the incident azimuth angle of the whistle detection echo signal in the p-th biomimetic communication and detection integrated signal relative to the array. m (t) represents the noise at the m-th element, m = 1, 2, ..., M, where M is the number of elements in the array. The array output covariance matrix B = E[x(t)x H (t)], E[·] represents the mean operation, and the superscript H represents transpose and conjugate; For each array element, the target azimuth angle is estimated using the incoherent signal subspace method: the bandwidth of the broadband signal is divided into J sub-bands, and for the center frequency f... j The subband covariance matrix B(f) j Perform eigenvalue decomposition, B(f) j )=U(f j )Λ(f j )U(f j ) H , j = 1, 2, ..., J; where, the eigenvector U(f j )=[U S (f j )U N (f j )], eigenvalues U S (f j ) represents the signal feature vector, U N (f j ) represents the noise feature vector, Λ S (f j ) represents the signal characteristic value, Λ N (f j ) represents the noise characteristic value; When the direction vector a(f) j When the Euclidean distance between (θ) and the signal subspace is minimized, a high spectral peak is obtained at the azimuth angle θ; using the spatial spectrum of each sub-band Obtain the broadband spatial spectrum An angular scan of the broadband spatial spectrum is performed to find the peak position of the spatial spectrum. The incident angle of the signal corresponding to the peak is the estimated value of the target azimuth angle.

4. The biomimetic covert underwater acoustic communication and detection integrated method as described in claim 3, characterized in that, The specific process of step (6) is as follows: (6-1) Calculated using the modulated signal of the ticking sound and the local signal of the ticking sound. N1 The cross-correlation function values ​​are used to obtain the location of the correlation peak and estimate the local signal number of the ticking sound; the inverse mapping between the local signal number of the ticking sound and the binary sequence is used to decode the N1-bit information. (6-2) Using the position t of the correlation peak of the adjacent x-th and x′=x+1-th tick modulated signals x and t x′ And the corresponding pulse width T of the modulated signal x and T x′ The time delay difference between the two ticking modulated signals is obtained. Using pulse position expression The q value is obtained, and the N2-bit information is demodulated by using the inverse mapping between q and the binary sequence. (6-3) Short-time Fourier transform is used to perform time-frequency shape analysis to determine the local whistle signal corresponding to the time-frequency shape; the inverse mapping between the time-frequency shape and the binary sequence is used to decode the N4-bit information of the bionic whistle modulated signal. (6-4) Calculate the 2 using the whistle local signal and the bionic whistle modulated signal determined in (6-3). N3 The local signal number of the whistle is estimated using the cross-correlation function values; the N3-bit modulation information is demodulated using the inverse mapping between the local signal number of the whistle and the binary sequence.

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