An OFDM sound source distance and depth estimation method based on a single hydrophone

Abstract

The present invention relates to the field of underwater acoustic positioning technology, and discloses an OFDM sound source distance and depth estimation method based on a single hydrophone, aiming to achieve parallel processing of communication and positioning tasks and efficient utilization of underwater time-frequency resources, and to promote the development of lightweight and low-power consumption devices suitable for underwater unmanned small platforms. The OFDM sound source distance and depth estimation method based on a single hydrophone proposed by the present invention combines the frequency-domain input-output relationship of a communication system under a multipath channel, uses comb-shaped pilots to construct an observation model for target positioning, constructs a multi-snapshot measurement matrix through spatial smoothing means, realizes multipath delay estimation based on the rotational invariance subspace algorithm, and then uses the channel delay feature matching method to achieve target positioning. The OFDM sound source distance and depth estimation method based on a single hydrophone provided by the present invention is applicable to the integrated information processing of a single hydrophone, has the advantages of miniaturization, lightweight, and portability, and is suitable for underwater unmanned small platforms.

Description

Technical Field

[0001] The present invention relates to the technical field of underwater acoustic positioning, and in particular to an OFDM sound source distance and depth estimation method based on a single hydrophone. Background Art

[0002] Communication and positioning are basic requirements in underwater acoustic applications. Although they have been comprehensively studied for many years, they have often been regarded as independent technical systems. In recent years, the integrated integration of communication and positioning functions has attracted a lot of research interest in underwater acoustic wireless transmission systems. Compared with the traditional independent technical route, the integrated solution can deeply couple communication and sensing capabilities through the introduction of dual-functional waveforms. On the one hand, it promotes the full utilization of spectrum resources and adapts to underwater acoustic channels with limited available bandwidth; at the same time, it is conducive to the parallel processing of communication and positioning tasks and improves the operation efficiency of the traditional time-division system. At the hardware level, the integrated waveform can use a set of equipment to complete the transceiver processing, reducing the volume, weight and power consumption of the system, and highly adapting to underwater unmanned platforms. A trend is that the application of small-sized devices (such as single vector or single scalar sensors) on submersibles has become a research hotspot.

[0003] Based on this, for the integrated information processing of a single hydrophone, the present invention uses an OFDM signal with high spectrum utilization efficiency as the dual-functional waveform, and proposes an OFDM sound source distance and depth estimation method based on a single hydrophone, which provides effective environmental sensing capabilities while meeting the high-speed communication requirements with the embedded pilot subcarriers. Summary of the Invention

[0004] To achieve the deep integration of communication and positioning functions, the present invention proposes an OFDM sound source distance and depth estimation method based on a single hydrophone. Specifically, based on the OFDM frequency-domain input-output relationship in a multipath channel, a measurement model for source localization is constructed using pilot information. A multi-snapshot measurement matrix is constructed by means of spatial smoothing, and multipath time delay estimation is realized based on the rotational invariance subspace algorithm. To reduce the requirement for high cooperation between the transceiver ends in the communication system, a method of matching the relative time delay characteristics of the channel is used to achieve target localization.

[0005] To achieve the object of the present invention, the technical solution of the present invention is as follows:

[0006] The OFDM sound source distance and depth estimation method based on a single hydrophone provided by the present invention includes the following steps:

[0007] S1. Use ray acoustics to formulate a three-path propagation channel model in a shallow water scenario, including a direct sound path and surface and bottom reflection sound paths;

[0008] S2. Based on the frequency-domain input-output relationship of the OFDM system, use pilot information to construct a measurement model for source localization;

[0009] S3. Construct a multi-snapshot measurement matrix through spatial smoothing means, and implement multipath delay estimation based on the rotational invariance subspace algorithm;

[0010] S4. Implement target positioning by using the channel relative delay feature matching method.

[0011] Preferably, the three-path propagation channel model assumes that the bottom and water surface in the observation area are horizontal, the sound speed is uniformly distributed, and the sound ray propagates along a straight line.

[0012] Preferably, the measurement model is based on the coarse synchronization before OFDM demodulation, obtains the signal arrival time, and constructs the input-output relationship in the frequency domain.

[0013] Preferably, the multi-snapshot measurement matrix is constructed by dividing the observation vector into overlapping sub-vectors, and the Vandermonde form and translational invariance characteristics of equally spaced pilots in the frequency domain are utilized.

[0014] Preferably, the multipath delay estimation is implemented through singular value decomposition and the rotational invariance subspace algorithm to obtain the time offset parameter estimation value.

[0015] Preferably, the target positioning is based on the relative delay feature matching method, and the source azimuth estimation is realized by minimizing the objective function.

[0016] Compared with the related technologies, the OFDM sound source distance and depth estimation method based on a single hydrophone provided by the present invention has the following beneficial effects:

[0017] The single hydrophone source localization scheme proposed by the present invention, compared with the existing localization schemes based on long baseline, (ultra) short baseline, towed array, and vertical array, does not require array calibration and high-precision clock synchronization. The equipment used has the advantages of miniaturization, light weight, and portability, has the ability to be installed on small underwater unmanned platforms, and further reduces the data processing burden.

[0018] The scheme proposed by the present invention can realize source localization while performing OFDM communication. Compared with the existing time-division communication and positioning systems, the overall operation efficiency of the system is higher, and the azimuth information update frequency is faster. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is the overall processing flow chart of an OFDM sound source distance and depth estimation method based on a single hydrophone provided by the present invention;

[0020] Figure 2 is the schematic diagram of the communication and positioning integrated scenario in the present invention;

[0021] Figure 3 is the schematic diagram of the pool test results in the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0022] The present invention will be further described below with reference to the accompanying drawings.

[0023] Please refer to Figure 1 , a method for estimating the distance and depth of an OFDM sound source based on a single hydrophone proposed by the present invention includes the following steps:

[0024] S1. Use ray acoustics to formulate a three-path propagation channel model for the shallow water scenario, including the direct sound path and the water surface and bottom reflection sound paths;

[0025] S2. Based on the frequency-domain input-output relationship of the OFDM system, use pilot information to construct a measurement model for source localization;

[0026] S3. Construct a multi-snapshot measurement matrix through spatial smoothing means, and implement multipath delay estimation based on the rotational invariance subspace algorithm;

[0027] S4. Use the channel relative delay feature matching method to achieve target localization.

[0028] The specific implementation manner of the solution of the present invention will be further described below with reference to the accompanying drawings.

[0029] (1) As shown in the following figure, assume that the bottom and the water surface in the observation area are horizontal, the water depth is , the sound speed is uniformly distributed, and at this time the sound ray propagates in a straight line. Let the heights of the receiving end and the transmitting end from the bottom be and respectively, and the horizontal distance is , . A three-path propagation channel will be composed of the direct sound path, the water surface and the bottom reflection paths. The above assumptions approximately hold in short-distance shallow water transmission.

[0030] (2) Assume that the transceiver ends are stationary during the positioning period, and the azimuth of the transmitting end relative to the receiving end is . For underwater acoustic high-frequency communication signals, ray acoustics theory is used for modeling. If the channel state is relatively stable and there are transmission paths (mainly considering the case of ), then the time-invariant channel impulse response can be expressed as

[0031]

[0032] In the above formula is the impulse function, are the multipath delays arranged from small to large and different from each other, and represents the path intensity.

[0033] (3) The receiver needs to perform coarse synchronization to obtain the signal arrival time before performing OFDM demodulation , if the signal transmission time is , the resulting time offset is . Characterizing the multipath structure of the channel is the basis for realizing single hydrophone source positioning.

[0034] (4) For an OFDM symbol, let The baseband frequency of the equally spaced comb pilot subcarriers is , the training symbol carried is After preprocessing such as down-conversion, low-pass filtering, and OFDM demodulation, the frequency domain input-output relationship of the communication system can be obtained. Since the channel is time-invariant, it is assumed that no inter-subcarrier interference is generated during OFDM demodulation. Subsequently, only the pilot subcarriers are considered and the input and output vectors are divided by the training symbols at the same time, and a typical frequency domain measurement model can be obtained:

[0035]

[0036] in To measure the noise ( represents a complex domain), , , l = 1, 2, … , L is the time deviation The phase shift generated on each pilot subcarrier ( is the transpose symbol), The complex-valued path gain Composition, of which is the carrier frequency.

[0037] (5) Considering the formula For a single snapshot model, to apply the subspace method, we need to construct a model with a rank greater than Note that the equally spaced pilots in the frequency domain make It has a Vandermonde form. Based on its translation invariance, the spatial domain smoothing method can be used to restore the rank of the matrix. Assume that the smoothing times are ( ), then the observation vector Divide into Overlapping subvectors , Include No. arrive elements. Then it is constructed as follows :

[0038]

[0039] (6) Can be analogized as the measurement matrix obtained by sensors through times of sampling. According to the subspace method, should be eigen-decomposed to obtain the eigen-matrix , where represents the conjugate transpose of the matrix. The above operation can be simplified to perform singular value decomposition on , and the obtained left singular vector matrix is .

[0040] (7) Sort the column vectors in in descending order of singular values. Since it is assumed that , the first three columns in are the signal subspace matrix, and the rest are the noise subspace matrix. Based on the rotational invariance subspace algorithm, the time offset parameter estimation value can be obtained.

[0041] (8) If absolute time offset is used for positioning, time synchronization is required at both the transmitter and receiver ends, and it is necessary to ensure that the receiver end can obtain the accurate transmission time of the signal. This will limit the application scenarios of the method to some extent, and since is generally in the order of milliseconds, the overall time error of the system needs to be controlled at a low level to ensure that it will not cause serious contamination. For the above considerations, the present invention designs the algorithm based on relative time delay. The relative time delay of the th path signal with respect to the first-arrival signal can be defined as .

[0042] (9) Denote . Note that when the sound field is fully predictable, is a function of. Therefore, the feature matching method based on relative time delay can be expressed as

[0043]

[0044] Let the that minimizes the above formula be the final positioning result.

[0045] (10) Considering that the theoretical minimum value of under noise-free conditions is 0. To construct a thumbtack-shaped spatial spectrum similar to MUSIC, the objective function can be written as

[0046]

[0047] Based on the above formula, the estimated value of the sound source azimuth will be completed through spectral peak search.

[0048] Compared with the related technologies, the OFDM sound source distance and depth estimation method based on a single hydrophone provided by the present invention has the following beneficial effects:

[0049] Compared with the existing positioning schemes based on long baseline, (ultra) short baseline, towed array, and vertical array, in the single hydrophone sound source positioning scheme proposed by the present invention, there is no need for array calibration and high-precision clock synchronization. The equipment used has the advantages of miniaturization, light weight, and portability, and has the ability to be installed on small underwater unmanned platforms, and further reduces the data processing burden.

[0050] The scheme proposed by the present invention can achieve sound source positioning while performing OFDM communication. Compared with the existing time-division communication and positioning systems, the overall operation efficiency of the system is higher, and the azimuth information update frequency is faster.

[0051] As Figure 3 shows the pool test results of the proposed method. The water depth of the pool is 5 m, the sound source and the hydrophone are 3 m from the pool bottom, and they are 5.7 m apart. Since the pool bottom and the water surface are not acoustically treated, sound waves will produce a multipath propagation effect in the pitch angle domain. It can be seen from the figure that the proposed method has a thumbtack-shaped spatial spectrum and gives a relatively accurate positioning result, and the positioning error is about 5% of the slant range.

[0052] The above are only the embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. A method for estimating the distance depth of an OFDM sound source based on a single hydrophone, characterized in that: The following steps are involved: S1. Use ray acoustics to develop a three-path propagation channel model in shallow water scenarios, including the direct sound path and the water surface and bottom reflection sound paths: Assume that the bottom and surface of the water in the observation area remain horizontal and the water depth is , speed of sound Evenly distributed, the sound line propagates in a straight line. Assume that the heights of the receiving end and the transmitting end from the bottom of the water are and , the horizontal distance is , The above assumption is approximately valid in shallow water short-distance transmission; assuming that both the transmitter and receiver are stationary during the positioning period, the relative position of the transmitter to the receiver is For underwater high-frequency communication signals, ray acoustics theory is used to model them. If the channel state is relatively stable, there is transmission paths, the time-invariant channel impulse response is expressed as ， In the above formula is the impulse function, are multipath delays arranged from small to large and different from each other, represents the path strength; S2. Based on the frequency domain input-output relationship of the OFDM system, the pilot information is used to build a measurement model for sound source localization: the receiver needs to perform coarse synchronization to obtain the signal arrival time before performing OFDM demodulation , if the signal transmission time is , the resulting time offset is ; Characterizes the multipath structure of the channel; for an OFDM symbol, let The baseband frequency of the equally spaced comb pilot subcarriers is , the training symbol carried is ; After down-conversion, low-pass filtering, and OFDM demodulation preprocessing, the frequency domain input-output relationship of the communication system is obtained; since the channel is time-invariant, it is assumed that no inter-subcarrier interference is generated during OFDM demodulation; then, only the pilot subcarriers are considered and the input and output vectors are simultaneously divided by the training symbols to obtain the frequency domain measurement model: ， in To measure the noise, represents the complex domain, , , l = 1, 2, … , L is the time deviation The phase shift produced on each pilot subcarrier, is the transpose symbol, The complex-valued path gain Composition, of which is the carrier frequency; S3. A multi-snapshot measurement matrix is ​​constructed by spatial domain smoothing, and multipath delay estimation is realized based on a rotationally invariant subspace algorithm. Specifically, the spatial domain smoothing method is: Assume the number of smoothing times is , , then the observation vector Divide into Overlapping subvectors , Include No. arrive elements, and then constructed as follows : ， By analogy The sensor The measurement matrix obtained by subsampling is Perform eigendecomposition to obtain the characteristic matrix ,in represents the matrix conjugate transpose, the above operation is simplified to Perform singular value decomposition, and the resulting left singular vector matrix is ; S4, using the channel relative delay feature matching method to achieve target positioning: in descending order of singular values The column vectors are sorted, because , The first three columns are signal subspace matrices, and the rest are noise subspace matrices; Based on the rotation invariant subspace algorithm, the estimated value of the time deviation parameter is obtained ; Using absolute time deviation When positioning, the time synchronization between the sending and receiving ends is required to ensure that the receiving end can obtain the accurate transmission time of the signal. ;No. The relative delay of the path signal relative to the first-reaching signal is defined as , For the The time offset of the path signal, is the time offset of the first path signal, For the The multipath delay of the signal along each path, is the multipath delay of the first path signal; remember , when the sound field is sufficiently predictable, for Function of The channel relative delay feature matching method is expressed as: ， Let the above formula be the smallest This is the final positioning result; Considering the noise-free condition The theoretical minimum value of is 0. To construct a pin-shaped spatial spectrum similar to MUSIC, the objective function is written as ， Based on the above formula, the estimation of the sound source direction will be completed by spectrum peak searching.

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