Sonar echo signal storage method, device and storage medium

Abstract

This application relates to a method, apparatus, and storage medium for storing sonar echo signals. The method includes: acquiring multiple sonar echo signals and dividing each signal into multiple signal subdomains; extracting effective data density values ​​from each signal subdomain and determining a signal to be compressed from the multiple signals based on the effective data density values; dividing the signal to be compressed into multiple signal subblocks; determining a target subblock within the signal subblocks, and adjacent subblocks within the signal subblocks that are adjacent to the target subblock; performing prediction processing on the point signal of the target subblock based on the adjacent subblocks to obtain a prediction block; determining residual block data based on the target subblock and the prediction block; and generating compressed data and storing it based on the residual block data and the target subblock. This application solves the problems of large data volume and low storage efficiency of high-throughput sonar echo signals in deep-sea exploration scenarios, improving the data compression ratio and storage efficiency while ensuring signal recovery quality.

Description

Technical Field

[0001] The present application relates to the field of signal and information processing, and in particular to a sonar echo signal storage method, device and storage medium. Background Art

[0002] With the development of deep-sea exploration technology, sonar systems have been widely used in the fields of ocean research, resource exploration, and environmental monitoring. By emitting sound waves and receiving their echoes, sonar systems can effectively detect underwater objects, measure water depth, topography, and other information. However, as the depth of ocean exploration continues to increase, signal acquisition, processing, compression, and storage face a series of challenges.

[0003] Traditional data storage solutions often fail to meet the needs of real-time transmission and efficient storage when processing high-throughput data generated by deep-sea exploration. Due to the high-dimensional characteristics and diversity of deep-sea exploration sonar echo signals, simple storage methods not only take up a lot of storage space, but may also lead to data redundancy. In addition, in the specific scenario of high frame rate, multi-beam, and real-time simulation imaging of deep-sea sonar echo signals, interference factors such as background noise and seabed reverberation in the deep-sea environment increase the complexity of signal processing, and signal processing needs to meet high real-time requirements (30FPS, single-frame data compression time is required to be within 30ms), while the compression time of single-frame signals in traditional compression coding algorithms is relatively long, and it is often impossible to achieve ideal compression efficiency and recovery quality at the same time.

[0004] At present, no effective solution has been proposed for how to solve the problems of large data volume and low storage efficiency of high-throughput sonar echo signals in deep-sea exploration scenarios. Summary of the invention

[0005] The embodiments of the present application provide a sonar echo signal storage method, device, system, electronic device and storage medium to at least solve the problem of how to solve the large amount of data and low storage efficiency of high-throughput sonar echo signals in deep-sea exploration scenarios in the related art.

[0006] In a first aspect, an embodiment of the present application provides a sonar echo signal storage method, comprising:

[0007] Acquire a plurality of the sonar echo signals, and divide each of the sonar echo signals into a plurality of signal sub-domains;

[0008] Extracting an effective data density value in each of the signal subdomains, and determining a signal to be compressed from a plurality of the sonar echo signals based on the effective data density value;

[0009] Dividing the signal to be compressed into a plurality of signal sub-blocks; determining a target sub-block among the plurality of signal sub-blocks, and adjacent sub-blocks adjacent to the target sub-block among the plurality of signal sub-blocks;

[0010] Predicting the point signal of the target sub-block according to the adjacent sub-blocks to obtain a prediction block; determining residual block data based on the target sub-block and the prediction block;

[0011] Compressed data is generated and stored according to the residual block data and the target sub-block.

[0012] In some embodiments, generating and storing compressed data according to the residual block data and the target sub-block includes:

[0013] Performing frequency domain conversion processing on the residual block data to obtain residual frequency data;

[0014] Based on a preset frequency threshold, low-frequency data is determined from the residual frequency data; and according to the low-frequency data and the target sub-block, the compressed data is generated and stored.

[0015] In some embodiments, determining low-frequency data from the residual frequency data based on a preset frequency threshold comprises:

[0016] Determining high frequency data based on a comparison result between the frequency threshold and the residual frequency data;

[0017] Based on a frequency screening rule, the high-frequency data is removed from the residual frequency data to obtain the low-frequency data.

[0018] In some embodiments, extracting the effective data density value in each of the signal subdomains, and determining the signal to be compressed from the plurality of sonar echo signals based on the effective data density value, comprises:

[0019] Determining the effective data density value of each of the signal sub-domains based on the data value of each of the sonar echo signals;

[0020] Based on the effective data density value, determining the signal quality parameter and effective data distribution area set corresponding to each of the sonar echo signals;

[0021] The signal to be compressed is determined from a plurality of the sonar echo signals based on the signal quality parameter and the set of valid data distribution areas.

[0022] In some embodiments, the step of determining the effective data density value of each signal sub-domain based on the data value of the sonar echo signal comprises:

[0023] Based on the comparison result between the data value of each sonar echo signal and a preset valid data threshold, the valid data density value of each signal sub-domain is determined.

[0024] In some embodiments, determining the signal quality parameter and the valid data distribution area set corresponding to each of the sonar echo signals based on the valid data density value includes:

[0025] Based on the data values ​​of each of the sonar echo signals, obtaining a signal average data value;

[0026] Based on the effective data density value and the signal average data value, the signal quality parameter is obtained, and the effective data distribution area set is obtained.

[0027] In some embodiments, determining the signal to be compressed from a plurality of the sonar echo signals based on the signal quality parameter and the set of valid data distribution areas includes:

[0028] Calculating a similarity value between every two sonar echo signals based on the signal quality parameter and the valid data distribution area set;

[0029] Based on the comparison result between the similarity value and a preset similarity threshold, the signal to be compressed is determined.

[0030] In some embodiments, the step of performing prediction processing on the point signal of the target sub-block according to the adjacent sub-blocks to obtain the predicted block includes:

[0031] Acquire a directional feature between the adjacent sub-block and the target sub-block;

[0032] Based on the directional feature, prediction processing is performed on the point signal where the target sub-block is located to obtain the prediction block corresponding to the target sub-block.

[0033] In a second aspect, an embodiment of the present application provides a sonar echo signal storage device, comprising:

[0034] A signal screening module, used for acquiring a plurality of the sonar echo signals, and dividing each of the sonar echo signals into a plurality of signal sub-domains;

[0035] The signal screening module is further used to extract the effective data density value in each of the signal sub-domains, and determine the signal to be compressed from the plurality of sonar echo signals based on the effective data density value;

[0036] A compression module, configured to divide the signal to be compressed into a plurality of signal sub-blocks; determine a target sub-block among the plurality of signal sub-blocks, and adjacent sub-blocks adjacent to the target sub-block among the plurality of signal sub-blocks;

[0037] The compression module is further used to perform prediction processing on the point signal of the target sub-block according to the adjacent sub-blocks to obtain a prediction block; and determine residual block data based on the target sub-block and the prediction block;

[0038] A storage module is used to generate and store compressed data according to the residual block data and the target sub-block.

[0039] In a third aspect, an embodiment of the present application provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the sonar echo signal storage method as described in the first aspect above.

[0040] Compared with the related art, the sonar echo signal storage method provided in the embodiment of the present application solves the problem of large data volume and low storage efficiency of high-throughput sonar echo signals in deep-sea exploration scenarios by means of effective data density value evaluation, signal quality parameter determination, data screening, sub-block division and predictive compression, improves the data compression ratio and storage efficiency, and ensures the signal recovery quality.

[0041] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0043] Figure 1 It is a hardware structure block diagram of a terminal of the sonar echo signal storage method according to an embodiment of the present invention;

[0044] Figure 2 is a flow chart of a sonar echo signal storage method according to an embodiment of the present application;

[0045] Figure 3 It is a preferred structural block diagram of a sonar echo signal storage method according to a preferred embodiment of the present application;

[0046] Figure 4 It is a structural block diagram of a sonar echo signal storage device according to an embodiment of the present application. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application. In addition, it can also be understood that although the efforts made in this development process may be complex and lengthy, for ordinary technicians in the field related to the contents disclosed in the present application, some changes such as design, manufacturing or production based on the technical contents disclosed in the present application are only conventional technical means, and should not be understood as insufficient contents disclosed in the present application.

[0048] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0049] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantity limitation, and may indicate the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application means greater than or equal to two. "And / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, "A and / or B" can mean: A exists alone, A and B exist at the same time, and B exists alone. The terms "first", "second", "third" and the like involved in the present application are merely used to distinguish similar objects and do not represent a specific ordering of the objects.

[0050] The method embodiment provided in this embodiment can be executed in a terminal, a computer or a similar computing device. Taking running on a terminal as an example, Figure 1 FIG. 1 is a hardware structure block diagram of a terminal of the sonar echo signal storage method according to an embodiment of the present invention. Figure 1 As shown, the terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Optionally, the terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is for illustration only and does not limit the structure of the above terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0051] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the sonar echo signal storage method in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the terminal via a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0052] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0053] This embodiment provides a sonar echo signal storage method. Figure 2 is a flow chart of a sonar echo signal storage method according to an embodiment of the present application, such as Figure 2 As shown, the process includes the following steps:

[0054] Step S201, acquiring multiple sonar echo signals, and dividing each sonar echo signal into multiple signal sub-domains;

[0055] Among them, this step transmits sound waves through the sonar system and receives echo signals reflected from the seabed or other underwater objects. These echo signals contain rich underwater environmental information. The sonar echo signal can be expressed as a two-dimensional array, dimension one (or row) is the number of analog-to-digital conversion modules, and dimension two (or column) is the number of timing points. The number of analog-to-digital conversion modules indicates how many independent channels or sensors in the sonar system are receiving sound signals at the same time. The number of timing points indicates how many time points or sampling points are recorded in the output of each analog-to-digital conversion module. Each timing point corresponds to the intensity or phase information of the sound wave signal received by the sonar system at a specific time point. Since the original signal is usually large and complex, it is difficult to process it directly, so each received sonar echo signal is divided into multiple signal sub-domains. The division process of the sonar echo signal is based on the time and space characteristics of the signal, that is, the time series (the number of time points) and the signal source (the number of analog-to-digital conversion modules). By dividing the sonar echo signal, the original two-dimensional sonar echo signal can be divided into smaller signal units that are easier to manage and process. The number of sub-areas can be determined according to the size of the sonar echo signal to be processed. For example, the sonar echo signal to be processed 256 4096 (byte data bits) are divided into 16 equal-sized sub-areas, each with a size of 256 256 (data bits).

[0056] This step divides the sonar echo signal into multiple signal subdomains, which can be processed in parallel later, improving the efficiency of signal processing and making subsequent data analysis and processing more accurate and efficient. By dividing the signal subdomains, the data parts that need to be stored and processed can be selected more flexibly, avoiding unnecessary data redundancy and thus reducing storage requirements.

[0057] Step S202, extracting the effective data density value in each signal subdomain, and determining the signal to be compressed from multiple sonar echo signals based on the effective data density value;

[0058] Among them, for each signal subdomain (i.e., an area in a two-dimensional array), first determine the valid data therein, which is the data point whose signal strength is greater than a preset background noise threshold X; calculate the percentage of valid data points in each signal subdomain, and this percentage is the effective data density value of the signal subdomain. Based on the extracted effective data density value, the signal quality of each sonar echo signal can be further analyzed. A signal quality parameter can be obtained by calculating the average value of the effective data density values ​​of all subregions of each sonar echo signal, and multiplying this average value with the overall numerical average value of the sonar echo signal. According to the signal quality parameter, those signals with higher signal quality and more effective information are screened out from multiple sonar echo signals as signals to be compressed.

[0059] This step can avoid unnecessary compression processing of low-quality and low-information-content signals by extracting the effective data density value and determining the signal to be compressed based on it, thereby improving the overall efficiency of data compression; by screening the signals to be compressed, it can ensure that the stored data has high signal quality and information content, providing a more valuable data basis for subsequent data analysis and processing. Only compressing and storing signals with higher signal quality can significantly reduce the storage space occupied, which is particularly important for application scenarios such as deep-sea exploration that generate huge amounts of data.

[0060] Step S203, dividing the signal to be compressed into a plurality of signal sub-blocks; determining a target sub-block among the plurality of signal sub-blocks, and adjacent sub-blocks adjacent to the target sub-block among the plurality of signal sub-blocks;

[0061] After the sonar echo signals to be compressed are determined, in order to perform compression processing more effectively, similar to the division process in the previous step, these signals are subdivided into smaller signal sub-blocks. Specifically, the size of a single signal sub-block is M. M (M=4, 8, 16, etc.), the smaller the value of M, the more precise the prediction of the echo information in the frame, but the coding efficiency and data compression rate will also decrease accordingly, so the specific value of M can be selected according to actual needs and data characteristics. In the two-dimensional matrix of the signal to be compressed, some target sub-blocks and adjacent sub-blocks around these target sub-blocks are selected. The target sub-block is the sub-block used for prediction, and the adjacent sub-block is the sub-block that is spatially adjacent to the target sub-block, which can be the sub-block above and to the left of the target sub-block. The distance between the adjacent sub-block and the target sub-block is less than or equal to M. The target sub-block can be selected based on the effective data density value or signal quality parameter of each signal sub-block; for example, the sub-block whose effective data density value is greater than the preset density threshold W in each signal sub-block can be selected as the target sub-block, such as the effective data density values ​​of the 9 sub-domains in a sonar echo signal are X1, X2...X9, respectively, where the values ​​of X2, X4, and X8 are greater than W, then X2, X4, and X8 are selected as the target sub-block; then the adjacent sub-blocks of the target sub-block are determined using the spatial correlation position of each signal sub-block in the two-dimensional matrix. This step can more accurately identify and process important information in the signal by dividing the signal to be compressed into multiple signal sub-blocks and determining the target sub-block and its adjacent sub-blocks, which helps to reduce redundant data, improve compression efficiency, and thus save storage space.

[0062] Step S204, predicting the point signal of the target sub-block according to the adjacent sub-blocks to obtain a predicted block; determining residual block data based on the target sub-block and the predicted block;

[0063] Among them, the point signal is the data value of the sonar echo signal at a specific time point or spatial position. The directional characteristics of the adjacent sub-blocks and the target sub-block can be used for linear interpolation or other prediction algorithms to generate the point signal in the prediction block with the same position as the target sub-block. For example, by linear interpolation of the adjacent sub-blocks above and to the left of the target sub-block, each point signal data in the prediction block with the same position as the target is generated. This step does not require the use of all signal sub-blocks. The more sub-blocks are used, the worse the compression effect, but the higher the signal restoration degree. After obtaining the predicted block, it is compared with the actual data of the target sub-block to calculate the difference between the two, that is, the residual block data.

[0064] This step has high computational efficiency through prediction processing and determination of residual block data, and can complete the prediction processing and determination of residual block data in a shorter time, supporting real-time or quasi-real-time compression and storage requirements of deep-sea exploration sonar echo signals; and the residual usually has less redundant information than the original data, which can significantly reduce the amount of data that needs to be stored; and by using the spatial correlation of adjacent data for prediction, the redundancy of the data can be further reduced, thereby improving the compression efficiency.

[0065] Step S205: Generate compressed data according to the residual block data and the target sub-block and store the compressed data.

[0066] Among them, the residual block data contains information in the target sub-block that is not accurately captured by the prediction block, and the compressed data includes the residual block data and the target sub-block. This step stores the anchor data block information used for prediction calculation, that is, the target sub-block, so that the original data can be reconstructed during decoding, and by storing only the residual block data and the target sub-block, the amount of data is significantly reduced, thereby achieving efficient data compression and reducing the required storage space.

[0067] Through the above steps, firstly, the high-quality signal area is screened out by the effective data density value, and then the spatial correlation of the signal is used to perform efficient compression to realize the compressed storage of the data. By screening and compressing the effective data, the unnecessary data processing amount is reduced, and the efficiency and speed of data storage are improved. The effective data density value and the signal quality parameters of the target object are used as reference factors for screening the sonar echo signal, so that the screened sonar echo signal can meet the quality requirements of effective compressed storage; and based on the spatial correlation of the data in the sonar echo signal frame, the data directional characteristics of adjacent sub-blocks are used for predictive compression, which improves the compression performance of the data, significantly reduces data redundancy, and thus reduces the demand for storage space.

[0068] In some embodiments, generating and storing compressed data according to the residual block data and the target sub-block includes:

[0069] Performing frequency domain conversion processing on the residual block data to obtain residual frequency data;

[0070] Based on a preset frequency threshold, low-frequency data is determined from the residual frequency data; and compressed data is generated and stored according to the low-frequency data and the target sub-block.

[0071] Among them, the residual block data is subjected to integer discrete cosine transform, that is, frequency domain conversion processing, to convert the residual signal data into several frequency components, and the residual frequency data is obtained as an N N matrix, each matrix coefficient represents a different frequency component in the residual block, wherein the low-frequency component usually contains the main information and is located in the upper left corner of the matrix, while the high-frequency component represents details and noise and is located in the lower right corner of the matrix, so it is necessary to screen out the low-frequency component containing the main information, so as to further optimize the compressed sonar echo signal. Through the preset frequency threshold Q, the frequency component with a frequency less than the preset frequency threshold is regarded as low-frequency data, and then the determined low-frequency data is encoded together with the target sub-block data used for prediction calculation to further reduce the amount of data, and the encoded low-frequency data and target sub-block data are stored as compressed data. This embodiment screens out the low-frequency data containing the main energy and characteristics of the signal and stores it, so that in the decoding and recovery process, the main information of the original signal can be better retained, thereby optimizing the recovery quality; screening the low-frequency data further reduces the amount of compressed data, which means that the required storage space is also reduced accordingly, thereby reducing the storage cost; and because the compression process is relatively simple and efficient, it can meet the requirements for real-time data processing in deep-sea exploration.

[0072] In some embodiments, determining low-frequency data from residual frequency data based on a preset frequency threshold comprises:

[0073] Determine high frequency data based on a comparison result between the frequency threshold and the residual frequency data;

[0074] Based on the frequency screening rule, high-frequency data is removed from the residual frequency data to obtain low-frequency data.

[0075] Among them, the residual frequency data is traversed, and each frequency component is compared with the preset frequency threshold. If a certain frequency component is greater than or equal to the frequency threshold Q, it is marked as high-frequency data. The frequency screening rule is to set the high-frequency data to 0, and the remaining data is non-zero value, that is, the low-frequency data (frequency is less than the frequency threshold Q) is recorded as non-zero value, and the residual frequency data is arranged in the order of "Z" shape as a one-dimensional array, and non-zero value (low-frequency data) is processed first. In addition, the frequency threshold Q can be adjusted. Q is used to measure the compression quality. As the Q value increases, more high-frequency components are ignored, and the compression efficiency is further increased. The higher the Q value, the higher the compression rate, and the lower the Q value, the more complete the signal, and more details of the signal will be retained. In this embodiment, by removing high-frequency noise, the low-frequency data is purer, and often contains the main features of the signal, such as trend, cycle, etc. In the decoding and recovery process, the main information of the original signal can be better retained, thereby optimizing the recovery quality. Screening low-frequency data also reduces the amount of compressed data and reduces the required storage space.

[0076] In some embodiments, extracting the effective data density value in each signal subdomain, and determining the signal to be compressed from a plurality of sonar echo signals based on the effective data density value, comprises:

[0077] Determine an effective data density value of each signal sub-domain based on the data value of each sonar echo signal;

[0078] Based on the effective data density value, determine the signal quality parameter and effective data distribution area set corresponding to each sonar echo signal;

[0079] Based on the signal quality parameter and the effective data distribution area set, a signal to be compressed is determined from a plurality of sonar echo signals.

[0080] Among them, valid data is determined based on the data value of each signal subdomain, and the percentage of valid data in each signal subdomain is calculated to obtain the valid data density value; the signal quality parameter is calculated based on the valid data density value; based on the valid data density value of each signal subdomain, the valid data distribution area set is determined, and the distribution area set is a two-dimensional array S[n[a]], where dimension one (or row) is the sonar echo signal, the number of rows is the number of signals n, and dimension two (or column) is the valid data density value of the signal subdomain, and the number of columns is the number of subdomains of the data in a single signal a, that is, an n A two-dimensional array of a. By using signal quality parameters and a set of effective data distribution areas to screen multiple sonar echo signals, redundant signals with a similarity exceeding a certain threshold and signals with large differences in signal quality parameters and effective data distribution area sets can be removed, thereby obtaining a signal to be compressed. This embodiment subdivides the signal area and calculates the effective data density value, uses the signal quality parameters to evaluate the overall quality of the signal, uses the effective data distribution area set to represent the distribution law of effective data, and finally screens based on these parameters to remove redundant and unnecessary signals, reduce the burden of data storage and transmission, and make the quality of the signal to be compressed higher, which is beneficial to the subsequent compression and recovery process, and also improves the real-time and efficiency of data processing, meeting the needs of deep-sea exploration.

[0081] In some embodiments, determining an effective data density value of each signal sub-domain based on a data value of a sonar echo signal includes:

[0082] Based on the comparison result between the data value of each sonar echo signal and the preset effective data threshold, the effective data density value of each signal sub-domain is determined.

[0083] The preset effective data threshold is G, and data greater than G in the data value of the sonar echo signal is determined as effective data, and the percentage of effective data in each signal subdomain to all data is calculated, and the calculation result is the effective data density value of the corresponding signal subdomain. By subdividing the signal area and calculating the effective data density value, this embodiment can more accurately evaluate the signal quality and provide a basis for subsequent signal screening and compression.

[0084] In some embodiments, based on the effective data density value, determining the signal quality parameter and the effective data distribution area set corresponding to each sonar echo signal includes:

[0085] Based on the data values ​​of each sonar echo signal, a signal average data value is obtained;

[0086] Based on the effective data density value and the signal average data value, a signal quality parameter is obtained, and a set of effective data distribution areas is obtained.

[0087] Among them, the average data value of the sonar echo signal to be processed is calculated, and the average value of the effective data density value of each sub-area is multiplied by the average data value to obtain the signal quality parameter corresponding to each sonar echo signal. At the same time, based on the effective data density value of each target sonar echo signal sub-area, the effective data distribution area set S[n[a]] is determined. In this embodiment, the signal quality parameter reflects the overall quality of the signal, and the effective data distribution area set reveals the distribution law of the effective data in the signal. These parameters and sets provide an important basis for subsequent signal screening and compression, which helps to improve compression efficiency and recovery quality.

[0088] In some of the embodiments, determining a signal to be compressed from a plurality of sonar echo signals based on a signal quality parameter and a set of valid data distribution areas includes:

[0089] Based on the signal quality parameter and the effective data distribution area set, the similarity value of each two sonar echo signals is calculated;

[0090] Based on the comparison result between the similarity value and the preset similarity threshold, a signal to be compressed is determined.

[0091] The process of calculating the similarity value of sonar echo signal A and sonar echo signal B is as follows: in the set of valid data distribution areas, the number of signals is 10 (n=10), the number of subdomains of each signal is 9 (a=9), and the signal quality parameter M of sonar echo signal A is calculated. A , the calculation formula is as follows:

[0092] M A =(X1+X2+......+X9) Y, where Y is the average data value of the signal, and X1, X2...X9 are the effective data density values ​​of the 9 sub-domains in signal A.

[0093] Similarly, the signal quality parameter M of the sonar echo signal B is calculated B , compared with M A With M B, and obtain the difference D% (i.e., similarity value), which can reflect the closeness of the two signals in data distribution and quality; set a similarity threshold R% to determine whether the two sonar echo signals are similar enough to be considered redundant. If the difference value D% is greater than or equal to R%, the current target sonar echo signal A or B is discarded, and the same operation is performed multiple times to obtain the signal to be compressed. By calculating the similarity value, this embodiment can identify those sonar echo signals with similar content and possible redundancy, and effectively remove those redundant sonar echo signals, thereby reducing the storage space occupied, while ensuring the validity and integrity of the data and improving the data compression efficiency; because the similarity comparison is based on the signal quality parameter and the effective data distribution area set, this method can more accurately identify redundant signals and avoid the accidental deletion of important data; in addition, this embodiment can also adjust the preset similarity threshold according to actual needs to adapt to different application scenarios and data characteristics.

[0094] In some of the embodiments, predicting the point signal of the target sub-block according to the adjacent sub-blocks to obtain the predicted block includes:

[0095] Obtaining directional features between adjacent sub-blocks and target sub-blocks;

[0096] Based on the directional characteristics, the point signal where the target sub-block is located is predicted and processed to obtain a prediction block corresponding to the target sub-block.

[0097] Among them, whether there is a directional feature between the adjacent sub-block and the target sub-block, such as the spatial position in the horizontal direction, vertical direction, diagonal direction, etc., can be identified by calculating the directional gradient, and the adjacent sub-blocks of the target sub-block (such as the adjacent sub-blocks above and to the left of the target sub-block) are linearly interpolated based on the directional gradient, thereby generating each point signal data in the prediction block with the same target position, that is, the prediction block corresponding to the target sub-block. In this embodiment, the directional feature can reveal the local structure of the signal data, which helps to more accurately predict the content of the target sub-block. By identifying and utilizing the directional feature, the amount of data that needs to be encoded or transmitted can be reduced, because similar sub-blocks can be represented by reference or residual coding. Compared with directly encoding the entire signal data, the present application can significantly reduce the overall computational complexity.

[0098] The embodiments of the present application are described and illustrated below through preferred embodiments.

[0099] Step S1, obtaining multiple sonar echo signals.

[0100] Step S2: determining an effective data density value of each sonar echo signal sub-region based on the data value of each sonar echo signal sub-region.

[0101] Step S3, determining the signal quality parameter of each sonar echo signal and the effective data distribution area set based on the product of the effective data density value of each sonar echo signal sub-area and the average data value of the sonar echo signal.

[0102] Step S4, filtering the sonar echo signal according to the above data to obtain the sonar echo signal to be compressed.

[0103] Step S5, based on the time-series continuous correlation of the internal data of the echo signal, linear fitting prediction is performed using the directional characteristics of adjacent data. Further, the residual between the real block and the predicted block is converted from the time domain to the frequency domain, and the low-frequency information and the internal sub-block data used for correlation calculation are stored.

[0104] S2 may include the following steps:

[0105] (1) The sonar echo signal to be processed is divided into a plurality of sub-areas, and the sonar echo signal to be processed is any signal among the plurality of sonar echo signals.

[0106] For example, the sonar echo signal to be processed can be divided into multiple sub-areas of equal size, and the size of each sub-area can be 30 30 (byte data bits), can also be 40 40 (byte data bits), can also be 50 50 (byte data bit), or other sizes, which are not limited here. The number of sub-areas can be determined according to the size of the sonar echo signal to be processed. For example, the sonar echo signal to be processed can be 256 4096 (byte data bits) are divided into 16 equal-sized sub-areas, and the size of each sub-area is 256 256 (byte data bits).

[0107] (2) Determine the valid data in each sub-area of ​​the sonar echo signal to be processed. The valid data must be higher than the custom background noise X, and the percentage of valid data is determined as the valid data density value of this sub-area.

[0108] S3 may include the following steps:

[0109] (1) Calculate the average data value of the sonar echo signal to be processed.

[0110] (2) Multiplying the average value of the effective data density values ​​of each sub-region of the sonar echo signal to be processed by the average data value of the sonar echo signal to determine the signal quality parameter of the sonar echo signal to be processed.

[0111] (3) Add the sub-region valid data density value to the valid data distribution area set of the sonar echo signal.

[0112] (4) The number of the multiple sonar echo signals to be processed is n. Based on the n sonar echo signals and the set of valid data distribution areas in the n sonar echo signals s[n[a]], p redundant sonar echo signals with a similarity greater than R% are removed, where a is the number of sub-areas, n is a positive integer greater than or equal to 1 and less than or equal to m, p is a positive integer greater than or equal to 0 and less than or equal to n-2, and R is a positive integer greater than or equal to 0 and less than or equal to 99%;

[0113] Determine the difference D% in signal quality parameters and valid data distribution area elements between the current target sonar echo signal and the previous and next signals, where D is a positive integer greater than or equal to 0 and less than or equal to 99%. If the difference value D% is greater than or equal to R%, the current target sonar echo signal is discarded to obtain the sonar echo signal to be compressed.

[0114] S4 may include the following steps:

[0115] (1) The sonar echo signal to be compressed is further divided into multiple sub-blocks.

[0116] For example, the size of a single sub-block is M M, supports M=4, 8, 16. The smaller the value, the more precise the prediction of intra-frame echo information, but the coding efficiency and data compression rate will also decrease.

[0117] (2) Based on the spatial correlation of the data around the sub-block, the directional characteristics of the adjacent data are used for prediction. The data of each point in the prediction block with the same position as the sub-block is generated by linear interpolation of the data block values ​​above and to the left of the sub-block. Obviously, this step does not require the use of all sub-blocks. The more sub-blocks are used, the worse the compression effect and the higher the signal restoration degree. Subtract the original sub-block from the prediction block to obtain the residual block.

[0118] (3) Perform integer discrete cosine transform on the residual block to convert the residual signal into several frequency components. After the residual block is transformed by integer discrete cosine transform, an M M matrix, each coefficient represents a different frequency component in the block, where the low-frequency component usually contains the main information and is located in the upper left corner of the matrix, while the high-frequency component represents details and noise and is located in the lower right corner of the matrix.

[0119] (4) Set the threshold Q, set the high-frequency component coefficients (frequency greater than or equal to Q) to 0, arrange these coefficients in a one-dimensional array in a "Z" shape, record the non-zero values, the number of non-zero values ​​is W, encode these W non-zero values, so that the non-zero low-frequency components are processed first, and the compression of the sonar echo signal is further optimized. In addition, as the Q value increases, more high-frequency components are ignored, and the compression efficiency is further increased. Finally, the sub-blocks used for prediction calculations and the residual frequency domain data are stored.

[0120] Figure 3 is a preferred structural block diagram of a sonar echo signal storage method according to a preferred embodiment of the present application, such as Figure 3 As shown, the sonar echo signal storage method includes the following modules:

[0121] An acquisition module 301 is used to acquire a plurality of sonar echo signal data;

[0122] A first determination module 302 is used to determine an effective data density value of each sonar echo signal sub-region based on the data value of each sonar echo signal sub-region;

[0123] A second determination module 303 is used to determine a signal quality parameter of each sonar echo signal based on the effective data density value of each sonar echo signal sub-region and the sonar echo signal numerical average value;

[0124] The third determination module 304 is used to determine a set of sonar echo signal valid data distribution areas based on the valid data density value of each target sonar echo signal sub-area;

[0125] The sonar echo signal screening module 305 is used to screen out the sonar echo signal to be compressed from the multiple sonar echo signals based on the valid data density values ​​of the multiple sonar echo signal sub-areas, the signal quality parameters of the sonar echo signals, and the set of sonar echo signal valid data distribution areas.

[0126] The sonar echo signal compression storage module 306 is used to perform linear data prediction based on the spatial correlation of the sub-block data and the directional characteristics of the adjacent database. Further, the residual between the real block and the predicted block is converted from the time domain to the frequency domain, and the residual low-frequency information and the database data information used for the prediction calculation are stored, and the encoded information is stored in the device.

[0127] This embodiment also provides a sonar echo signal storage device, which is used to implement the above embodiments and preferred implementations, and will not be repeated here. As used below, the terms "module", "unit", "subunit", etc. can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0128] Figure 4 is a structural block diagram of a sonar echo signal storage device according to an embodiment of the present application, such as Figure 4 As shown, the device comprises:

[0129] A signal screening module 10 is used to obtain a plurality of sonar echo signals and divide each sonar echo signal into a plurality of signal sub-domains;

[0130] The signal screening module 10 is further used to extract the effective data density value in each signal subdomain, and determine the signal to be compressed from the multiple sonar echo signals based on the effective data density value;

[0131] The compression module 20 is used to divide the signal to be compressed into a plurality of signal sub-blocks; determine a target sub-block among the plurality of signal sub-blocks, and adjacent sub-blocks adjacent to the target sub-block among the plurality of signal sub-blocks;

[0132] The compression module 20 is also used to perform prediction processing on the point signal of the target sub-block according to the adjacent sub-blocks to obtain a prediction block; based on the target sub-block and the prediction block, determine the residual block data;

[0133] The storage module 30 is used to generate and store compressed data according to the residual block data and the target sub-block.

[0134] The storage module 30 is further used to determine low-frequency data from the residual frequency data based on a preset frequency threshold; generate and store compressed data according to the low-frequency data and the target sub-block.

[0135] The storage module 30 is further used to determine the high frequency data based on the comparison result between the frequency threshold and the residual frequency data;

[0136] Based on the frequency screening rule, high-frequency data is removed from the residual frequency data to obtain low-frequency data.

[0137] The above-mentioned screening signal module 10 is also used to determine the effective data density value of each signal sub-domain based on the data value of each sonar echo signal;

[0138] Based on the effective data density value, determine the signal quality parameter and effective data distribution area set corresponding to each sonar echo signal;

[0139] Based on the signal quality parameter and the effective data distribution area set, a signal to be compressed is determined from a plurality of sonar echo signals.

[0140] The signal screening module 10 is further used to determine the effective data density value of each signal sub-domain based on the comparison result between the data value of each sonar echo signal and the preset effective data threshold.

[0141] The above-mentioned screening signal module 10 is also used to obtain a signal average data value based on the data values ​​of each sonar echo signal;

[0142] Based on the effective data density value and the signal average data value, a signal quality parameter is obtained, and a set of effective data distribution areas is obtained.

[0143] The above-mentioned signal screening module 10 is also used to calculate the similarity value of every two sonar echo signals based on the signal quality parameter and the effective data distribution area set;

[0144] Based on the comparison result between the similarity value and the preset similarity threshold, a signal to be compressed is determined.

[0145] The compression module 20 is also used to obtain directional characteristics between adjacent sub-blocks and the target sub-block;

[0146] Based on the directional characteristics, the point signal where the target sub-block is located is predicted and processed to obtain a prediction block corresponding to the target sub-block.

[0147] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0148] In addition, in combination with the sonar echo signal storage method in the above embodiment, the embodiment of the present application can provide a storage medium for implementation. The storage medium stores a computer program; when the computer program is executed by a processor, any one of the sonar echo signal storage methods in the above embodiment is implemented.

[0149] Those skilled in the art should understand that the technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0150] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A sonar echo signal storage method, characterized in that: include: Acquire a plurality of the sonar echo signals, and divide each of the sonar echo signals into a plurality of signal sub-domains; Extracting an effective data density value in each of the signal subdomains, and determining a signal to be compressed from a plurality of the sonar echo signals based on the effective data density value; Dividing the signal to be compressed into a plurality of signal sub-blocks; determining a target sub-block among the plurality of signal sub-blocks, and adjacent sub-blocks adjacent to the target sub-block among the plurality of signal sub-blocks; Predicting the point signal of the target sub-block according to the adjacent sub-blocks to obtain a prediction block; determining residual block data based on the target sub-block and the prediction block; Compressed data is generated and stored according to the residual block data and the target sub-block.

2. The sonar echo signal storage method according to claim 1, characterized in that: The step of generating compressed data according to the residual block data and the target sub-block and storing the compressed data comprises: Performing frequency domain conversion processing on the residual block data to obtain residual frequency data; Based on a preset frequency threshold, low-frequency data is determined from the residual frequency data; and according to the low-frequency data and the target sub-block, the compressed data is generated and stored.

3. The sonar echo signal storage method according to claim 2, characterized in that: The step of determining low-frequency data from the residual frequency data based on a preset frequency threshold comprises: Determining high frequency data based on a comparison result between the frequency threshold and the residual frequency data; Based on a frequency screening rule, the high-frequency data is removed from the residual frequency data to obtain the low-frequency data.

4. The sonar echo signal storage method according to claim 1, characterized in that: The step of extracting the effective data density value in each of the signal subdomains and determining the signal to be compressed from the plurality of sonar echo signals based on the effective data density value comprises: Determining the effective data density value of each of the signal sub-domains based on the data value of each of the sonar echo signals; Based on the effective data density value, determining the signal quality parameter and effective data distribution area set corresponding to each of the sonar echo signals; The signal to be compressed is determined from a plurality of the sonar echo signals based on the signal quality parameter and the set of valid data distribution areas.

5. The sonar echo signal storage method according to claim 4, characterized in that: The step of determining the effective data density value of each signal sub-domain based on the data value of the sonar echo signal comprises: Based on the comparison result between the data value of each sonar echo signal and a preset valid data threshold, the valid data density value of each signal sub-domain is determined.

6. The sonar echo signal storage method according to claim 4, characterized in that: The determining, based on the effective data density value, of a signal quality parameter and an effective data distribution area set corresponding to each of the sonar echo signals comprises: Based on the data values ​​of each of the sonar echo signals, obtaining a signal average data value; Based on the effective data density value and the signal average data value, the signal quality parameter is obtained, and the effective data distribution area set is obtained.

7. The sonar echo signal storage method according to claim 4, characterized in that: The step of determining the signal to be compressed from a plurality of the sonar echo signals based on the signal quality parameter and the set of valid data distribution areas comprises: Calculating a similarity value between every two sonar echo signals based on the signal quality parameter and the valid data distribution area set; Based on the comparison result between the similarity value and a preset similarity threshold, the signal to be compressed is determined.

8. The sonar echo signal storage method according to claim 1, characterized in that: The step of performing prediction processing on the point signal of the target sub-block according to the adjacent sub-blocks to obtain a prediction block includes: Acquire a directional feature between the adjacent sub-block and the target sub-block; Based on the directional feature, prediction processing is performed on the point signal where the target sub-block is located to obtain the prediction block corresponding to the target sub-block.

9. A sonar echo signal storage device, characterized in that: include: A signal screening module, used for acquiring a plurality of the sonar echo signals, and dividing each of the sonar echo signals into a plurality of signal sub-domains; The signal screening module is further used to extract the effective data density value in each of the signal sub-domains, and determine the signal to be compressed from the plurality of sonar echo signals based on the effective data density value; A compression module, configured to divide the signal to be compressed into a plurality of signal sub-blocks; determine a target sub-block among the plurality of signal sub-blocks, and adjacent sub-blocks adjacent to the target sub-block among the plurality of signal sub-blocks; The compression module is further used to perform prediction processing on the point signal of the target sub-block according to the adjacent sub-blocks to obtain a prediction block; and determine residual block data based on the target sub-block and the prediction block; A storage module is used to generate and store compressed data according to the residual block data and the target sub-block.

10. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the sonar echo signal storage method according to any one of claims 1 to 8 when executed.

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