CN111580110A - Composite code underwater acoustic ranging method based on shallow sea multipath time delay - Google Patents
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Abstract
The invention discloses a composite code underwater acoustic ranging method based on shallow sea multipath time delay, which adopts a composite ranging code as a synchronous ranging sequence, modulates and filters the composite ranging code, circularly transmits the composite ranging code through an underwater acoustic multipath channel, and respectively carries out FFT (fast Fourier transform) on a received signal and a local known signal to obtain a frequency domain signal-to-noise ratio estimation value of the corresponding received signal, a self-power spectral function and a cross-power spectral function of the received signal and the local signal; establishing a weighting function, performing frequency domain weighting processing on the cross-power spectrum function by using the weighting function, performing inverse Fourier transform on the weighted cross-power spectrum function, and performing peak detection on a real part of the transformed cross-power spectrum function so as to extract multipath time delay; according to the geometrical relationship between the multipath time delay and different propagation paths, the straight-line distance between the transmitting terminal and the receiving terminal is calculated by the multipath time delay and the known geographic environment data. The invention has low operation complexity, strong anti-interference capability and more accurate ranging performance.
Description
Technical Field
The invention relates to an underwater acoustic ranging method, in particular to a composite code underwater acoustic ranging method based on shallow sea multipath time delay.
Background
At present, accurate ranging and positioning between Underwater vehicles (AUV) have irreplaceable effects on completing some important tasks, and have important significance on realizing the synergistic effect of a plurality of vehicles and the like. However, in the face of an extremely complex underwater acoustic channel, especially an AUV for shallow water operation, the sonar-based ranging method is susceptible to underwater acoustic multipath, fast time-varying and other factors, and the implementation principle is relatively complex. Therefore, in order to reasonably adopt ocean waveguide information and reduce the influence of an underwater special environment on a ranging system and the complexity of a single-transmitting single-receiving ranging system, the method is one of important research directions for realizing accurate ranging between AUVs.
In the marine environment, the marine wave guides such as multipath effect and broadband scattering have a plurality of unique characteristics, wherein the multipath effect can be used for sound source positioning and has a good ranging effect. However, in a shallow sea environment, the underwater acoustic ranging method based on the multipath time delay still has great problems and challenges in the implementation processes of underwater acoustic signal synchronization, multipath time delay detection, correct matching of the multipath time delay and the like. First, in the underwater acoustic ranging technology, commonly used ranging signals include a single-frequency pulse signal, a chirp signal, a hyperbolic chirp signal, a pseudorandom spread spectrum signal, and the like. The single-frequency pulse signal has the characteristics of simplicity and practicability, but the signal cannot give consideration to the action distance and the ranging resolution, and the anti-interference capability is poor, so that higher application requirements cannot be met. Compared with linear frequency modulation and hyperbolic frequency modulation signals, the pseudorandom spread spectrum signals have advantages in time delay resolution and are a hot problem of research. In view of this, researchers have proposed that Kasami sequences are applied to an underwater acoustic positioning system as spreading sequences and correlation experiments are performed in the mediterranean region to prove excellent anti-noise performance, but the Kasami sequences do not have ideal autocorrelation characteristics and can reduce the performance of a ranging system when used as a synchronous transmission sequence of the ranging system. Then, researchers propose that an m sequence with better autocorrelation is used as a transmitting sequence to be applied to underwater acoustic communication, and propose a rapid synchronization algorithm to solve the bottleneck problem in the synchronization over-calculation process, but the computation load in the synchronization capturing process is still large, the signal change under the rapid time-varying condition of the shallow sea environment is difficult to track, and the requirement of real-time property is difficult to meet. Meanwhile, researchers put forward that M-element spread spectrum and code element shift keying spread spectrum are combined to be applied to the field of underwater sound synchronous spread spectrum, and a good effect is achieved. However, the correlation property of the M sequence is not ideal and is rarely applied to the underwater acoustic system alone. In addition, in view of the limitations of M-sequence and M-sequence in the pulse position modulation spread spectrum system, researchers propose to apply NH sequence with good aperiodic autocorrelation to the underwater acoustic communication system, and compare it with the traditional M-sequence based communication system, and verify its superior performance, but the NH sequence is more suitable for the narrowband underwater acoustic spread spectrum system. Then, in the underwater acoustic ranging system based on the shallow sea multipath time delay, the ranging error mainly comes from the detection of the multipath time delay, so that the realization of accurate detection of the multipath time delay has important significance for improving the ranging precision. Generally, the commonly used multipath delay detection algorithm mainly includes an adaptive method, a cross-correlation method, a cepstrum method, and the like. The self-adaptive method does not need prior knowledge of a transmitted signal, but needs longer adaptive time to achieve high-precision time delay estimation, and is difficult to meet the real-time property. The resolution of the cepstrum is better than that of the autocorrelation method in theory, but if the channel is distorted, the correlation among different paths is reduced, and the performance of the cepstrum is inferior to that of the autocorrelation method. In order to improve the accuracy of multipath delay detection, researchers have proposed a Generalized Cross-Correlation (GCC) delay estimation algorithm. The algorithm applies a weight or window function to the cross power spectrum, suppressing the noise power. The weights mainly include a Roth processor, a smooth coherent transform (SCOT), a phase transform (PHAT), and the like. The GCC algorithm is good in robustness, small in calculation amount and easy to implement in real time, but is easily influenced by shallow sea environment noise. In response to this problem, in recent years, many improved methods have been proposed by both domestic and foreign scholars. Researchers provide a GCC time delay estimation algorithm based on an improved wavelet threshold function, which can effectively inhibit noise, reduce the fluctuation of a generalized cross-correlation function and enable a peak value to be sharper, but the denoising of a signal is limited by wavelet basis selection and decomposition scale. Meanwhile, researchers propose that the correlation peak value is further improved through a Hilbert difference method, but Hilbert transformation needs complex recursion, the operation time is longer than that of short-time Fourier transformation, and real-time multipath time delay estimation is not facilitated. In addition, in the underwater acoustic ranging method based on the multipath time delay, the accurate matching of the multipath time delay and the propagation path is a precondition for realizing accurate ranging, but the multipath time delay detection algorithm cannot determine whether the multipath time delay is caused by sea surface reflection or seabed reflection.
Disclosure of Invention
The invention provides a composite code underwater acoustic ranging method which is strong in anti-interference capability and high in accuracy and is based on shallow sea multipath time delay, aiming at solving the technical problems in the prior art.
The technical scheme adopted by the invention for solving the technical problems in the prior art is as follows: a composite code underwater sound distance measurement method based on shallow sea multipath time delay adopts a composite distance measurement code as a synchronous distance measurement sequence, obtains a distance measurement transmitting signal after modulating and filtering the composite distance measurement code, circularly transmits the distance measurement transmitting signal from a transmitting terminal to a receiving terminal through an underwater sound multipath channel, and demodulates the receiving signal into a composite code underwater sound synchronous signal at the receiving terminal; carrying out FFT transformation on the received signal and the local signal respectively, and calculating to obtain a frequency domain signal-to-noise ratio estimation value of the corresponding received signal, a self-power spectrum function of the received signal and a self-power spectrum function of the local signal, and obtaining a cross-power spectrum function of the received signal and the local signal; establishing a weighting function by using the frequency domain signal-to-noise ratio estimation value, the self-power spectral function of the received signal and the self-power spectral function of the local signal, performing frequency domain weighting processing on the cross-power spectral function by using the weighting function, performing inverse Fourier transform on the cross-power spectral function after weighting processing, performing peak detection on the real part of the cross-power spectral function after transformation, and further extracting multipath time delay; according to the geometrical relationship between the multipath time delay and different propagation paths, the straight-line distance between the transmitting terminal and the receiving terminal is calculated by the multipath time delay and the known geographic environment data.
Further, let the self-power spectrum function of the received signal be Gyy(ω) setting the self-power spectral function of the local signal to Gxx(omega), the frequency domain signal-to-noise ratio estimation value is set as
The following weighting function is established:
wherein gamma is more than or equal to 0 and less than or equal to 1, and the functional relationship between the value of gamma and the estimated value of the signal-to-noise ratio of the frequency domain is as follows:
wherein:
γ0、γ1is constant, and γ1＞γ0、
The specific expression is as follows:
wherein, when applied in a shallow sea environment, θ0And theta1Is taken as0＝0dB，θ1＝5dB。
Further, a matching matrix is established according to all matching conditions between the multipath time delay and different propagation paths, a relational equation set between the multipath time delay and the propagation paths is obtained through the matching matrix, a matching function is established through the relational equation set, the size of the matching function value under different matching conditions is calculated, the multipath time delay corresponding to the minimum matching function value is matched with the propagation paths to be the best matching, and the linear distance between the transmitting end and the receiving end is calculated according to the extracted multipath time delay and the geometrical relationship between the different propagation paths through the best matching multipath time delay and the geographical environment data.
Further, the specific step of calculating the linear distance between the transmitting end and the receiving end includes:
a-1, calculating all corresponding matching conditions between the multipath time delay and the propagation path according to the extracted multipath time delay;
step A-2, establishing a matching matrix according to all corresponding matching conditions between the multipath time delay and the propagation path, wherein each row in the matching matrix represents one matching condition between the multipath time delay and the propagation path;
step A-3, when the multipath time delay is matched with the propagation path, writing a relation equation set between the multipath time delay and the propagation path according to the matching matrix, and setting k1～kiRepresenting the 1 st to i-th equations in the relation equation set;
step A-4, with k1～kiConstructing a matching function expressed as:
in the formula, M is the number of multipath time delays;
step A-5, calculating the matching function values under different matching conditions, wherein the matching condition corresponding to the matching function value being the minimum value under all the matching conditions is the correct matching condition of the multipath time delay and the propagation path;
step A-6, combining the extracted multipath time delay and the geometrical relationship existing between different propagation paths, adopting the multipath time delay delta tau with correct matchingiAnd calculating the straight-line distance between the transmitting and receiving ends according to the known geographic environment information.
Further, performing Boolean logic combination on the subcodes at the transmitting end to generate a composite ranging code; and multiplying the composite ranging code by the sine carrier signal, then performing binary phase shift keying modulation, and processing the modulated composite ranging code by a forming filter to obtain a ranging emission signal.
Further, at a receiving end, performing sliding correlation operation on the demodulated received signal and the local subcode to obtain a correlation value of the received signal and the local subcode to realize signal synchronization, then performing discrete Fourier transform on the received signal realizing the signal synchronization, averagely dividing a channel bandwidth into n sections, and setting the square of the average amplitude of the i-th section of channel received signal as AiI is 1,2 … n; let the average of the squares of the average amplitudes of the n segments be A0(ii) a The mean amplitude square value is larger than A0The plurality of sections are used as main frequency sections of the composite ranging code signal, the average value of the sections is calculated, and the average value is used as the power of the composite ranging code signal; the mean amplitude square value is less than A0The plurality of segments are used as frequency segments only containing noise signals, the mean value of the frequency segments is calculated, and the mean value is used as the noise power of the channel environment; and obtaining the frequency domain signal-to-noise ratio estimation value of the received signal according to the composite ranging code signal power and the noise power of the channel environment.
Further, the method for calculating the straight-line distance between the transmitting terminal and the receiving terminal by the multi-path time delay and the known geographic environment data comprises the following steps: setting the time delay difference between a direct path and a primary sea surface reflection path as delta tau in a DS method, a DB method and a DSB method1And the time delay difference between the direct path and the primary seabed reflection path is set to be delta tau2Setting the straight-line distance between the transmitting end and the receiving end as d;
by Δ τ1The method for calculating d is a DS method, and the calculation formula is as follows:
by Δ τ2The method for calculating d is a DB method, and the calculation formula is as follows:
by Δ τ1、Δτ2The method for calculating d is a DSB method, and the calculation formula is as follows:
wherein D is1＝2H1，D2＝2(H3-H1) (ii) a c is the speed of sound, H1And H2Depth, H, of the transmitting and receiving ends, respectively3Is shallow sea depth.
The invention has the advantages and positive effects that:
(1) the operation complexity is low: the invention provides a method for using a composite code as a synchronous transmitting sequence to be applied to an underwater sound ranging system aiming at the problem of large synchronous capturing computation amount when an m sequence is used as the transmitting sequence in the underwater sound ranging system, and supports a receiving end to quickly and accurately realize underwater sound signal synchronization.
(2) The anti-interference capability is strong: the invention provides a generalized cross-correlation multipath time delay detection algorithm for improving a weighting function aiming at the problem that the generalized cross-correlation multipath time delay detection algorithm is easily influenced by shallow sea environment noise, and the accuracy of multipath time delay detection in a low signal-to-noise ratio environment is improved. Meanwhile, a method for matching the multipath time delay with the propagation path is provided and applied to a composite code underwater acoustic ranging method of the shallow sea multipath time delay, so that the error of the ranging method is reduced.
Drawings
FIG. 1 is a block diagram of the working principle of a shallow sea multipath delay-based composite code underwater acoustic ranging method of the present invention;
FIG. 2 is a flow chart of the operation of a weighting function of the present invention;
FIG. 3 is a flow chart of a distance computation method for matching multipath delays in accordance with the present invention;
FIG. 4 is a diagram of an intrinsic acoustic line based on shallow sea multi-path time delay composite code underwater acoustic ranging;
FIG. 5 is a diagram illustrating the synchronization capture error rate of the composite code underwater acoustic synchronization signal;
fig. 6 is a performance diagram of the CC multi-path delay detection method when SNR is-5 dB;
fig. 7 is a schematic diagram of the performance of the GCC multipath delay detection algorithm using the PHAT weighting function when the SNR is-5 dB;
fig. 8 is a schematic diagram of the performance of the GCC multipath delay detection algorithm using the HB weighting function when the SNR is-5 dB;
FIG. 9 is a performance diagram of the composite code underwater acoustic ranging method using the multipath delay of the present invention when SNR is-5 dB
FIG. 10 is a diagram illustrating a comparison of multi-path delay detection performance of GCC algorithm with improved weighting;
FIG. 11 is a diagram illustrating the performance of the ranging method in channel A environment;
FIG. 12 is a diagram illustrating performance of a ranging method in a channel B environment;
FIG. 13 is a diagram illustrating performance of a ranging method in a channel C environment;
fig. 14 is a diagram illustrating performance of a ranging method in a channel D environment.
Detailed Description
For further understanding of the contents, features and effects of the present invention, the following embodiments are enumerated in conjunction with the accompanying drawings, and the following detailed description is given:
referring to fig. 1 to 14, a composite code underwater acoustic ranging method based on shallow sea multipath time delay adopts a composite ranging code as a synchronous ranging sequence, modulates and filters the composite ranging code to obtain a ranging transmission signal, circularly transmits the ranging transmission signal from a transmitting end to a receiving end through an underwater acoustic multipath channel, demodulates the received signal into a composite code underwater acoustic synchronous signal at the receiving end, and performs sliding correlation operation on the demodulated signal and a local sub-code to obtain a correlation value of the received signal and the local sub-code to realize signal synchronization; carrying out FFT transformation on a received signal for realizing signal synchronization and a local known signal respectively, and calculating to obtain a frequency domain signal-to-noise ratio estimation value of the corresponding received signal, a self-power spectrum function of the received signal and a self-power spectrum function of the local signal, and obtaining a cross-power spectrum function of the received signal and the local signal; establishing a weighting function by using the frequency domain signal-to-noise ratio estimation value, the self-power spectral function of the received signal and the self-power spectral function of the local signal, performing frequency domain weighting processing on the cross-power spectral function by using the weighting function, performing inverse Fourier transform on the cross-power spectral function after weighting processing, performing peak detection on the real part of the cross-power spectral function after transformation, and further extracting multipath time delay; according to the geometrical relationship between the multipath time delay and different propagation paths, the straight-line distance between the transmitting terminal and the receiving terminal is calculated by the multipath time delay and the known geographic environment data. FFT chinese paraphrasing is fast fourier transform.
Preferably, the self-power spectrum function of the received signal can be set to Gyy(ω) setting the self-power spectral function of the local signal to Gxx(omega), the frequency domain signal-to-noise ratio estimation value is set as
The following weighting function may be established:
wherein, gamma is more than or equal to 0 and less than or equal to 1, and the function relation between the value of gamma and the estimated value of the signal-to-noise ratio of the frequency domain can be as follows:
wherein:
γ0、γ1is constant, and γ1＞γ0、
γ0、γ1The specific value expression may be as follows:
wherein, when applied in shallow sea environment, theta is convenient for calculation0And theta1May take theta as a specific value0＝0dB，θ1＝5dB。
Signal cross-power spectral function G using modified weighting function psi (omega)xy(omega) carrying out frequency domain weighting processing, then carrying out inverse Fourier transform on the weighted signal cross-power spectral function, carrying out peak detection on the real part of the weighted signal cross-power spectral function, and further extracting the relative time delay tau between different pathsl，τlThe calculation formula of (c) can be as follows:
preferably, a matching matrix can be established according to all matching conditions between the multipath time delay and different propagation paths, a relational equation set between the multipath time delay and the propagation paths is obtained through the matching matrix, a matching function can be established through the relational equation set, the size of the matching function value under different matching conditions is calculated, the multipath time delay corresponding to the minimum matching function value can be matched with the propagation paths to be the best matching, and the linear distance between the transmitting end and the receiving end is calculated according to the extracted multipath time delay and the geometrical relationship between the different propagation paths through the best matching multipath time delay and the geographical environment data.
Preferably, the specific step of calculating the linear distance between the transmitting end and the receiving end may include:
a-1, calculating all corresponding matching conditions between the multipath time delay and the propagation path according to the extracted multipath time delay;
step A-2, establishing a matching matrix according to all corresponding matching conditions between the multipath time delay and the propagation path, wherein each row in the matching matrix represents one matching condition between the multipath time delay and the propagation path;
step A-3, when the multipath time delay is matched with the propagation path, writing a relation equation set between the multipath time delay and the propagation path according to the matching matrix, and setting k1～kiRepresenting the 1 st to i-th equations in the relation equation set;
step A-4, with k1～kiConstructing a matching function expressed as:
in the formula, M is the number of multipath time delays;
step A-5, calculating the matching function values under different matching conditions, wherein the matching condition corresponding to the matching function value being the minimum value under all the matching conditions is the correct matching condition of the multipath time delay and the propagation path;
step A-6, combining the extracted multipath time delay and the geometrical relationship existing between different propagation paths, adopting the multipath time delay delta tau with correct matchingiAnd calculating the straight-line distance between the transmitting and receiving ends according to the known geographic environment information.
Preferably, the sub-codes are subjected to Boolean logic combination at the transmitting end to generate a composite ranging code; and multiplying the composite ranging code by the sine carrier signal, then performing binary phase shift keying modulation, and processing the modulated composite ranging code by a forming filter to obtain a ranging emission signal. Binary phase shift keying modulation, abbreviated in english as BPSK.
Preferably, at the receiving end, the demodulated received signal and the local subcode are subjected to sliding correlation operation to obtain a correlation value of the received signal and the local subcode to realize signal synchronization, then discrete fourier transform is performed on the received signal to realize signal synchronization, the channel bandwidth is averagely divided into n segments, and the square of the average amplitude of the i-th segment of channel received signal is set as aiI is 1,2 … n; calculating the mean amplitude squared A of the received signal in each segmenti，AiThe calculation formula is as follows:
wherein, Y2(k) Is the amplitude of the received signal;
let the average of the squares of the average amplitudes of the n segments be A0(ii) a The mean amplitude square value is larger than A0The average value of the composite code ranging signal is calculated and used as the composite ranging code signal power and is marked as Py(ii) a The mean amplitude square value is less than A0The average value of the frequency segments of the channel environment is calculated and taken as the noise power of the channel environment, and is marked as Pv(ii) a And obtaining the frequency domain signal-to-noise ratio estimation value of the received signal according to the composite ranging code signal power and the noise power of the channel environment. I.e. by PyAnd PvCalculating the SNR of the received signal, wherein the calculation formula is as follows:
preferably, the method for calculating the straight-line distance between the transmitting end and the receiving end from the multipath time delay and the known geographical environment data comprises: setting the time delay difference between a direct path and a primary sea surface reflection path as delta tau in a DS method, a DB method and a DSB method1And the time delay difference between the direct path and the primary seabed reflection path is set to be delta tau2Setting the straight-line distance between the transmitting end and the receiving end as d;
by Δ τ1The method for calculating d is a DS method, and the calculation formula is as follows:
by Δ τ2The method for calculating d is a DB method, and the calculation formula is as follows:
by Δ τ1、Δτ2The method for calculating d is a DSB method, and the calculation formula is as follows:
wherein D is1＝2H1，D2＝2(H3-H1) (ii) a c is the speed of sound, H1And H2Depth, H, of the transmitting and receiving ends, respectively3Is shallow sea depth.
The working process and working principle of the present invention are further described below by a preferred embodiment of the present invention:
a composite code underwater acoustic ranging method based on shallow sea multipath time delay mainly takes a composite code with a period of 3255, which is formed by compounding subcodes with periods of 7, 15 and 31 respectively, as a synchronous transmitting sequence and a shallow sea environment sea depth of 100m as an example, and comprises the following steps:
step 1.1, transmitting terminal pair subcode C in ranging systemn(i) Performing Boolean logic combination to generate a composite ranging code C;
passing each subcode respectively through a period of LnForm a sequence Cn′(i)＝Cn(i mod Ln) The subcode is represented as CnLength of LnIn the Tausworthe composite code, n is more than or equal to 1 and less than or equal to 6, the invention adopts the composite code formed by compounding n-3 subcodes, and the logical combination formula of the composite code is
C＝sign(C1+C2+C3)
Wherein each subcode is C1＝+1+1+1-1-1+1-1，C 21+1+1-1-1+1-1+1+ 1-1-1+1-1+1 and C3＝+1+1+1-1-1+1-1+1+1+1-1-1+1-1+1+1+1+1-1-1+1-1+1+1+1-1-1+1-1+1+1。
And step 1.2, multiplying C by a sine carrier signal v (t) to complete BPSK modulation, wherein the definition in BPSK modulation is binary phase shift keying modulation. And (3) carrying out molding filtering processing on the modulated signal to obtain a ranging signal x (t), and finally circularly sending the x (t) to the underwater acoustic multipath channel, wherein the specific experimental parameter setting is shown in table 1.
TABLE 1 Experimental parameter settings
And 2, receiving the composite code underwater sound synchronous signal y (t) transmitted by different shallow sea multipath simulation channels by a receiving end in real time, wherein the specific simulation channel parameter setting is shown in table 2. Firstly, carrying out discrete Fourier transform on y (t), calculating the signal-to-noise ratio estimation value of the signal in a frequency domain, and adopting the signal-to-noise ratio estimation value and the self-power spectrum function G of the received signalyy(omega) and the self-power spectral function G of the local signalxx(omega) the improved weighting function psi (omega) is designed and then the psi (omega) is used to cross-power the signal spectral function Gxy(omega) carrying out frequency domain weighting processing, finally carrying out inverse Fourier transform on the weighted signal cross-power spectral function, carrying out peak detection on the real part of the weighted signal cross-power spectral function, and further extracting the multipath time delay taul. The method specifically comprises the following substeps:
step 2.1, receiving and demodulating the underwater sound synchronous signal of the composite code in real time at a receiving end, carrying out sliding correlation operation on the local subcode and the received composite code sequence to realize the real-time synchronization process of the underwater sound signal of the composite code, then carrying out discrete Fourier transform on the received underwater sound synchronous signal of the composite code, averagely dividing the channel bandwidth into i sections, and calculating the average amplitude square A of the received signal in each sectioniDefined as:
wherein, Y2(k) Is the amplitude of the received signal;
step 2.2, setting the square of the average amplitude of the i-th channel receiving signal as AiI is 1,2 … n; let the average of the squares of the average amplitudes of the n segments be A0(ii) a Will average the amplitudeSquare value greater than A0The average value of the composite code ranging signal is calculated and used as the composite ranging code signal power and is marked as Py(ii) a The mean amplitude square value is less than A0The average value of the frequency segments of the channel environment is calculated and taken as the noise power of the channel environment, and is marked as Pv(ii) a And obtaining the frequency domain signal-to-noise ratio estimation value of the received signal according to the composite ranging code signal power and the noise power of the channel environment. I.e. by PyAnd PvCalculating the SNR of the received signal, wherein the calculation formula is as follows:
step 2.3, calculating the self-power spectrum function G of the underwater sound synchronous signal of the received composite codeyy(omega) and the self-power spectral function G of the local signalxx(omega) and then using the signal-to-noise ratio estimate of the received signal, Gxx(omega) and Gyy(ω) a modified weighting function ψ (ω) is designed, expressed as:
wherein, gamma is more than or equal to 0 and less than or equal to 1, and the function relation between the value of gamma and the estimated value of the signal-to-noise ratio of the frequency domain can be as follows:
wherein:
γ0、γ1may be a constant determined according to the actual situation, and γ1＞γ0、
The specific expression may be as follows:
wherein, when applied in shallow sea environment, theta is convenient for calculation0And theta1May take theta as a specific value0＝0dB，θ1＝5dB。
Step 2.4, signal cross-power spectrum function G is subjected to improved weighting function psi (omega)xy(omega) carrying out frequency domain weighting processing, then carrying out inverse Fourier transform on the weighted signal cross-power spectral function, carrying out peak detection on the real part of the weighted signal cross-power spectral function, and further extracting the relative time delay tau between different pathslNamely:
step 2.5, the receiving end receives the composite code underwater sound synchronous signal propagated by different shallow sea multipath channels in real time, the specific simulation channel parameter setting is shown in table 2, the sliding correlation operation is carried out on the local subcode and the received composite code sequence to realize the real-time synchronization process of the composite code underwater sound signal, then the discrete Fourier transform is carried out on the received composite code underwater sound synchronous signal, the channel bandwidth is averagely divided into i sections, the average amplitude square A of the received signal in each section is calculatediDefined as:
TABLE 2 environmental parameters for channels A-D
Step 3, adopting the correctly matched multipath time delay to calculate the linear distance between the receiving and transmitting terminals, firstly, establishing a matching matrix P according to all the matching conditions between the extracted multipath time delay and different propagation paths, and adopting P to obtain a relation equation set k between the multipath time delay and the propagation paths1～kiThen, adopt k1～kiConstructing a matching function, calculating the sizes under different matching conditions, taking the corresponding matching condition when the minimum value is the condition that the multipath time delay is correctly matched with the propagation path, finally, combining the geometrical relationship existing between different propagation paths, adopting the correctly matched multipath time delay and the known geographic environment information to calculate the linear distance between the transmitting and receiving ends, referring to a table 2, respectively defining channels under four corresponding environments as a channel A, a channel B, a channel C and a channel D, and carrying out comparative analysis on the distance measuring method. The method specifically comprises the following substeps:
step 3.1, according to the extracted multipath time delay tau l1,2 … M calculates all the corresponding matching between the multipath delay and the propagation path, i.e. there is M | in total! In a matching situation, the invention extracts the relative time delay between a primary sea surface reflection path (S), a primary seabed reflection path (B) and a direct path (D), namely M is 2, so that the multipath time delay and the propagation path exist
A match condition is generated;
step 3.2, establishing a matching matrix P according to all corresponding matching conditions between the multipath time delay and the propagation path, wherein each row in P represents one matching condition between the multipath time delay and the propagation path, and delta d1、Δd2Path difference between the primary sea surface, the sea bottom reflection path and the direct path, respectively, P can be expressed as:
step 3.3, for the matching matrix P, when the multipath time delay is matched with the propagation path, a relation equation k between the multipath time delay and the propagation path can be written according to the geometrical relation between the P and a transmitting terminal, a receiving terminal and a virtual receiving terminal formed on the sea surface or the seabed1And k2The expression is as follows:
wherein, (x, y) is the coordinates of the transmitting end, (x)0,y0) As the receiver coordinates, (x)1,y1) And (x)2,y2) Forming coordinates of virtual receiving end terminals on the sea surface and the seabed for the receiving end respectively;
step 3.4, use k1And k2Constructing a matching function expressed as:
in the formula, | | | |, is a norm;
step 3.5, calculating the value of the matching function under different matching conditionskThen comparekAnd recording all matching caseskMinimum value of (1), denoted by min: (k)，＝min(k) The corresponding matching condition is the correct matching condition of the multipath time delay and the propagation path;
and 3.6, calculating the linear distance between the transmitting and receiving ends by adopting the correctly matched multipath time delay and the known geographic environment information by combining the geometrical relationship existing among different propagation paths.
(1) using the time delay difference delta tau between the direct path (D) and the primary sea surface reflection path (S)1Calculating the linear distance d between the transmitting and receiving ends, and recording the linear distance d as a DS method, namely:
wherein c is the speed of sound H1And H2The depths of the transmitting end and the receiving end are respectively;
(2) using the time delay difference Deltatau between the direct path (D) and the primary seafloor reflection path (B)2Calculating the straight-line distance d between the transmitting and receiving ends, and recording as a DB method, namely:
wherein H3Shallow sea depth;
(3) adopting the time delay difference delta tau between the direct path (D) and the primary sea surface reflection path (B) and the primary sea bottom reflection path1、Δτ2Calculating the straight-line distance d between the transmitting and receiving ends, and recording the straight-line distance d as a DSB method, namely:
wherein D is1＝2H1，D2＝2(H3-H1)
The invention firstly analyzes the calculation complexity which is provided by taking the composite code as a synchronous transmitting sequence and applying the composite code to an underwater sound ranging system to realize signal synchronization, and compares the calculation complexity with a m sequence with the same period as the underwater sound synchronous transmitting sequence to realize signal synchronization. For a composite code consisting of m-, n-, and p-th order m-sequences,correlation operation times T required by synchronous acquisition process1Comprises the following steps:
T1＝(2m-1)+(2n-1)+(2p-1)
the synchronous capture m sequence of the sliding correlation method is carried out in a shift correlation mode, namely serial sliding correlation among all the subcodes, so the number of correlation operation times T required for synchronously capturing m sequences with the same length2Comprises the following steps:
T2＝(2m-1)(2n-1)(2p-1)
by comparison, T is1Much less than T2Compared with the m sequence, the composite code is used as a synchronous transmitting sequence to realize the synchronization of the underwater sound signals, and has smaller computation amount and lower complexity.
Referring to fig. 4, under the conditions of shallow sea multipath and negative acoustic velocity gradient, the synchronous capture error rate of the composite code is simulated and calculated by 10000 monte carlo experiments in combination with real-time sampling data. Referring to fig. 5, N is the detection window size of the composite code synchronous acquisition, and M is the period of the M sequences. It can be known from the figure that the error rate of the composite code synchronous capture by the sliding correlation method is related to the size of the detection window of the receiving end, and the error rate of the composite code synchronous capture gradually decreases with the increase of the detection window, thus showing better synchronous capture performance. The error rate of the composite code synchronous capture is 0 under the shallow sea multipath environment with the detection window of 2000 and the signal-to-noise ratio of-10 dB, namely the accuracy is up to 100%, and the use requirement of the composite code underwater acoustic ranging is met. Therefore, when the underwater acoustic signal of the composite code is synchronously captured, the size of the detection window can be fixed to 2000, the underwater acoustic signal synchronization and the multi-path time delay extraction are realized, the accuracy of the composite code synchronous capture is ensured, and the data calculation amount of an underwater acoustic ranging system is further reduced. In addition, by comparing the error rate of the composite code with the error rate of the synchronous acquisition of the m sequence with the same period, the error rate of the synchronous acquisition of the composite code is smaller than that of the m sequence, i.e. the synchronous acquisition performance of the composite code is better than that of the m sequence with the same period.
In shallow sea multipath environment with channel B and SNR (signal to noise ratio) of-5 dB, the shallow sea-based method is adoptedThe underwater acoustic ranging method of the composite code of the multipath time delay carries out simulation experiments and compares and analyzes the method with a GCC multipath time delay detection algorithm of the traditional weighting function (CC, PHAT and HB). Referring to fig. 6 to 9, pseudo peaks appear in the correlation results output by the GCC algorithm of the CC algorithm, the PHAT weighting function, and the HB weighting function, and the maximum pseudo peak amplitudes are about 0.59, 0.51, and 0.53, respectively, so that the multi-path delay peak caused by the bottom reflection is submerged, and the multi-path delay τ cannot be correctly detected2. The composite code underwater acoustic ranging method based on the shallow sea multipath time delay of the invention has clear output correlation peak, obviously inhibits noise interference and can accurately detect all multipath time delays. Further, in order to better balance the performance of the GCC algorithm with the different weighting functions and verify the superiority of the GCC algorithm with the improved weighting functions, the Mean Square Error (MSE) of the GCC algorithm with the different weighting functions is calculated by performing 1000 monte carlo experiments under the condition of different signal to noise ratios, which is shown in fig. 10. When the signal-to-noise ratio is large (SNR)>10dB), the multi-path time delay mean square errors of the 4 multi-path time delay detection algorithms are smaller, but the mean square errors of the GCC time delay detection algorithms of the CC algorithm, the PHAT weighting function and the HB weighting function are increased rapidly along with the reduction of the signal-to-noise ratio, wherein the increase of the mean square error of the CC algorithm is most obvious, the GCC algorithm of the PHAT weighting function is second, and the mean square error of the GCC algorithm of the HB weighting function is smaller. In contrast, the composite code underwater acoustic ranging method based on the shallow sea multipath time delay has the minimum mean square error and better multipath time delay detection performance.
The method for correctly matching the multipath time delay with the propagation path, which is proposed by the invention, is subjected to simulation analysis in the environments of the channel A, the channel B, the channel C and the channel D, and the multipath time delay is obtained by respectively calculating and extracting through a Bellhop model, and is specifically shown in Table 3. Wherein, Δ τ1And Δ τ2Respectively representing the time delay difference between the reflected path and the direct path of the sound wave through the sea surface or the sea bottom once, and table 3 is arranged according to the size of the multipath time delay, namely delta tau2＞Δτ1. Then, the matching functions under different matching conditions are calculated, and the correct matching conditions are obtained by comparing the sizes of the matching functions. The specific calculation process is as follows: first according to the multipath delay values in Table 3And calculating by adopting known environmental parameters and combining a geometric method to obtain a vector k. And then, under different channel environments, the sizes of the matching functions are respectively calculated. And finally, taking the minimum matching condition as a correct matching condition.
TABLE 3 multipath time delays in channels A-D
Table 4 gives the calculated matching function sizes for each matching case. Wherein the matching function1Denotes. DELTA.tau1、Δτ2The corresponding propagation path is DSR, DBR, matching function2Denotes. DELTA.tau1、Δτ2The corresponding propagation paths are DBR, DSR. Matching function in channel A and channel B environment2Comparison, matching function1Is small, indicating that in the first matching case, a correct match between the multipath delay and the propagation path is achieved, Δ τ1、Δτ2The corresponding propagation path is DSR, DBR, i.e. Δ τ1Is the relative time delay, Δ τ, between the primary sea surface reflection path and the direct path2Is the relative time delay between the primary seafloor reflection path and the direct path. In the channel C environment, it can be known from the calculation result that in the first matching case, the correct matching between the multipath delay and the different paths is achieved, i.e. Δ τ1、Δτ2The corresponding propagation path is DSR, DBR. However, as the transceiving ends are respectively positioned at 40m and 50m under the water and are close to the middle depth position of the sea water, the time delay difference between the sound wave passing through the primary sea surface reflection path, the primary seabed reflection path and the direct path is small, and the matching function value calculated under the second error matching condition is smaller than that under other channel environments. Matching function under channel D environment with increasing depth of receiving and transmitting end1Comparison, matching function2Is small, which means that in the second matching case, the multipath delay is correctly matched to the different propagation paths, i.e. Δ τ1、Δτ2The corresponding propagation paths are DBR, DSR.
TABLE 4 matching function calculated in channel A-D Environment
On the basis of realizing the correct matching of the multipath time delay and the propagation path, in order to analyze the influence of different depth positions of the transceiving end under water on the performance of the underwater acoustic ranging method based on the shallow sea multipath time delay, composite code underwater acoustic ranging simulation experiments based on the shallow sea multipath time delay are respectively carried out in the channels A-D. Fig. 11 to 14 are graphs showing ranging performance of three distance settlement methods (DS, DB, DSB) in channels a-D, from which it can be seen that the depth of the transmitting and receiving end has a large influence on the ranging performance of the DS, DB, DSB method. When the underwater position of the receiving and transmitting end is closer to the sea surface, the distance error measured by the DB method is the smallest, the performance is optimal, but the distance error measured by the DB method is continuously increased along with the increase of the depth of the receiving and transmitting end; when the depth of the receiving and transmitting end is positioned at the middle position, the distance measurement errors of the 3 methods are not large; when the depth of the receiving and transmitting end is closer to the seabed, the distance error measured by adopting the DS method is minimum, and the performance is optimal. Therefore, in the actual test, the corresponding distance settlement method with better performance can be selected according to the depth of the transceiving end so as to reduce unnecessary ranging errors.
The above-mentioned embodiments are only for illustrating the technical ideas and features of the present invention, and the purpose thereof is to enable those skilled in the art to understand the contents of the present invention and to carry out the same, and the present invention shall not be limited to the embodiments, i.e. the equivalent changes or modifications made within the spirit of the present invention shall fall within the scope of the present invention.
Claims (7)
1. A composite code underwater acoustic ranging method based on shallow sea multipath time delay is characterized in that a composite ranging code is used as a synchronous ranging sequence, the composite ranging code is modulated and filtered to obtain a ranging transmitting signal, the ranging transmitting signal is circularly transmitted to a receiving end from the transmitting end through an underwater acoustic multipath channel, and the receiving signal is demodulated into a composite code underwater acoustic synchronous signal at the receiving end; carrying out FFT transformation on the received signal and the local signal respectively, and calculating to obtain a frequency domain signal-to-noise ratio estimation value of the corresponding received signal, a self-power spectrum function of the received signal and a self-power spectrum function of the local signal, and obtaining a cross-power spectrum function of the received signal and the local signal; establishing a weighting function by using the frequency domain signal-to-noise ratio estimation value, the self-power spectral function of the received signal and the self-power spectral function of the local signal, performing frequency domain weighting processing on the cross-power spectral function by using the weighting function, performing inverse Fourier transform on the cross-power spectral function after weighting processing, performing peak detection on the real part of the cross-power spectral function after transformation, and further extracting multipath time delay; according to the geometrical relationship between the multipath time delay and different propagation paths, the straight-line distance between the transmitting terminal and the receiving terminal is calculated by the multipath time delay and the known geographic environment data.
2. The method as claimed in claim 1, wherein the self-power spectrum function of the received signal is set as Gyy(ω) setting the self-power spectral function of the local signal to Gxx(omega), the frequency domain signal-to-noise ratio estimation value is set as
The following weighting function is established:
wherein gamma is more than or equal to 0 and less than or equal to 1, and the functional relationship between the value of gamma and the estimated value of the signal-to-noise ratio of the frequency domain is as follows:
wherein:
γ0、γ1is constant, and γ1＞γ0、
The specific expression is as follows:
wherein, when applied in a shallow sea environment, θ0And theta1Is taken as0＝0dB，θ1＝5dB。
3. The underwater acoustic composite code ranging method as claimed in claim 1, wherein a matching matrix is established according to all matching conditions between multipath delays and different propagation paths, a relational equation set between multipath delays and propagation paths is obtained from the matching matrix, a matching function is established from the relational equation set, the magnitude of the matching function value under different matching conditions is calculated, the multipath delay corresponding to the minimum matching function value is matched with the propagation paths to be the best match, and the linear distance between the transmitting end and the receiving end is calculated from the multipath delay and the geographical environment data which are the best match according to the extracted multipath delays and the geometrical relationship existing between different propagation paths.
4. The method as claimed in claim 3, wherein the step of calculating the linear distance between the transmitting end and the receiving end comprises:
a-1, calculating all corresponding matching conditions between the multipath time delay and the propagation path according to the extracted multipath time delay;
step A-2, establishing a matching matrix according to all corresponding matching conditions between the multipath time delay and the propagation path, wherein each row in the matching matrix represents one matching condition between the multipath time delay and the propagation path;
step A-3, when the multipath time delay is matched with the propagation path, writing a relation equation set between the multipath time delay and the propagation path according to the matching matrix, and setting k1～kiRepresenting the 1 st to i-th equations in the relation equation set;
step A-4, with k1～kiConstructing a matching function expressed as:
in the formula, M is the number of multipath time delays;
step A-5, calculating the matching function values under different matching conditions, wherein the matching condition corresponding to the matching function value being the minimum value under all the matching conditions is the correct matching condition of the multipath time delay and the propagation path;
step A-6, combining the extracted multipath time delay and the geometrical relationship existing between different propagation paths, adopting the multipath time delay delta tau with correct matchingiAnd calculating the straight-line distance between the transmitting and receiving ends according to the known geographic environment information.
5. The method of claim 1, wherein the sub-codes are subjected to boolean logic combination at the transmitting end to generate the composite ranging code; and multiplying the composite ranging code by the sine carrier signal, then performing binary phase shift keying modulation, and processing the modulated composite ranging code by a forming filter to obtain a ranging emission signal.
6. The shallow sea multipath time delay based composite code underwater acoustic ranging method as claimed in claim 1,at a receiving end, performing sliding correlation operation on the demodulated received signal and the local subcode to obtain a correlation value of the received signal and the local subcode to realize signal synchronization, then performing discrete Fourier transform on the received signal realizing the signal synchronization, averagely dividing the channel bandwidth into n sections, and setting the average amplitude square of the i-th section of channel received signal as AiI is 1,2 … n; let the average of the squares of the average amplitudes of the n segments be A0(ii) a The mean amplitude square value is larger than A0The plurality of sections are used as main frequency sections of the composite ranging code signal, the average value of the sections is calculated, and the average value is used as the power of the composite ranging code signal; the mean amplitude square value is less than A0The plurality of segments are used as frequency segments only containing noise signals, the mean value of the frequency segments is calculated, and the mean value is used as the noise power of the channel environment; and obtaining the frequency domain signal-to-noise ratio estimation value of the received signal according to the composite ranging code signal power and the noise power of the channel environment.
7. The method of claim 1, wherein the method of calculating the linear distance between the transmitting end and the receiving end from the multi-path delay and the known geographical environment data comprises: setting the time delay difference between a direct path and a primary sea surface reflection path as delta tau in a DS method, a DB method and a DSB method1And the time delay difference between the direct path and the primary seabed reflection path is set to be delta tau2Setting the straight-line distance between the transmitting end and the receiving end as d;
by Δ τ1The method for calculating d is a DS method, and the calculation formula is as follows:
by Δ τ2The method for calculating d is a DB method, and the calculation formula is as follows:
by Δ τ1、Δτ2The method for calculating d is a DSB partyThe calculation formula is as follows:
wherein D is1＝2H1，D2＝2(H3-H1) (ii) a c is the speed of sound, H1And H2Depth, H, of the transmitting and receiving ends, respectively3Is shallow sea depth.
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| CN114019453A (en) * | 2022-01-04 | 2022-02-08 | 山东科技大学 | Ranging method based on underwater acoustic baseline positioning system |
| CN114019453B (en) * | 2022-01-04 | 2022-04-22 | 山东科技大学 | Ranging method based on underwater acoustic baseline positioning system |
| CN117872379A (en) * | 2024-03-11 | 2024-04-12 | 西北工业大学青岛研究院 | Underwater target ranging method, medium and system under shallow sea internal wave condition |
| CN117872379B (en) * | 2024-03-11 | 2024-05-28 | 西北工业大学青岛研究院 | Underwater target ranging method, medium and system under shallow sea internal wave condition |
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