Underwater acoustic signal lossless compression method and device suitable for ocean monitoring

Abstract

The invention relates to the technical field of signal processing, in particular to an underwater acoustic signal lossless compression method suitable for ocean monitoring, which comprises the following steps: after ocean underwater acoustic signals are subjected to front-end amplification and filtering conditioning, the signals are acquired to form a data stream, and the acquired signal data stream is subjected to primary packaging in a segmented manner according to a time sequence; the load data in the packet is compressed, secondary packaging is carried out after compression is completed, and the secondary packaging comprises the steps of carrying out updating packaging on primary packaging information, updating packet header load length information, mean value information of the packet header added into the whole data segment, information of the occupied space of single data after compression and load data CRC verification information; and storing the secondarily packaged data packet into a signal storage module. By applying the method, the ocean monitoring data can be effectively compressed, and the data storage capacity and the communication bandwidth of the ocean monitoring equipment are reduced, so that the power consumption, the size and the cost of the ocean monitoring equipment are reduced, and the ocean monitoring equipment tends to be more practical.

Description

Technical Field

[0001] The present application relates to the field of signal processing technology, and in particular to a method and device for lossless compression of underwater acoustic signals suitable for ocean monitoring. Background Art

[0002] Existing ocean monitoring equipment stores the original signals after collecting them. Long-term underwater monitoring requires large-capacity storage devices, which consume a large proportion of power compared to ocean monitoring equipment. As a result, long-term ocean monitoring equipment consumes large power, has many batteries, and is large in size, making it difficult to deploy and recover, and has high costs.

[0003] For the low power consumption requirement, the communication bandwidth between the underwater main node and multiple sub-nodes is insufficient relative to the amount of raw data collected.

[0004] In view of this, how to provide a lossless underwater acoustic signal compression method suitable for ocean monitoring equipment, reduce the data storage capacity and communication bandwidth of ocean monitoring equipment, thereby reducing the power consumption, volume and cost of ocean monitoring equipment, and making ocean monitoring equipment more practical, has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] The embodiments of the present application provide a method for lossless compression of underwater acoustic signals suitable for ocean monitoring, and a device for lossless compression of underwater acoustic signals suitable for ocean monitoring, which are used to solve the problems of large storage capacity requirements, high power consumption, large size and high cost of current equipment.

[0006] In a first aspect of an embodiment of the present application, a method for lossless compression of underwater acoustic signals suitable for ocean monitoring is provided, comprising:

[0007] After the ocean acoustic signal is amplified, filtered and conditioned at the front end, the signal is collected to form a data stream, and the collected signal data stream is segmented and packaged once in chronological order, wherein header information and tail information are injected into the signal during the packaging;

[0008] Compress the payload data in the packet, and perform secondary packaging after the compression is completed, wherein the secondary packaging is to update the primary packaging information, update the payload length information of the packet header, add the mean value information of the entire data segment to the packet header, as well as the space size information of the compressed single data and the CRC check information of the payload data;

[0009] The data packet after secondary packaging is stored in the signal storage module, wherein the frame format of the data packet is the packet header of the first packaging, the mean information of the entire data segment, the space size information of the compressed single data, the payload data CRC check information, and the compressed payload data.

[0010] In a second aspect of an embodiment of the present application, a device for lossless compression of underwater acoustic signals suitable for ocean monitoring is provided, comprising:

[0011] The primary packaging module is configured to collect the ocean hydroacoustic signal to form a data stream after the front-end amplification, filtering and conditioning, and to perform a primary packaging on the collected signal data stream in segments in time sequence, wherein header information and tail information are injected into the signal during the primary packaging;

[0012] The secondary packaging module is configured to compress the payload data in the packet and perform secondary packaging after the compression is completed, wherein the secondary packaging is to update the primary packaging information, update the payload length information of the packet header, add the mean value information of the entire data segment to the packet header, as well as the space size information of the compressed single data and the CRC check information of the payload data;

[0013] The storage module is configured to store the data packet after secondary packaging into the signal storage module, wherein the frame format of the data packet is the packet header of the first packaging, the mean information of the entire data segment, the space size information of the compressed single data, the payload data CRC check information, and the compressed payload data.

[0014] The present application provides a method for lossless compression of underwater acoustic signals suitable for ocean monitoring, comprising: first, after the ocean underwater acoustic signal is amplified, filtered and conditioned at the front end, the signal is collected to form a data stream, and the collected signal data stream is segmented in time sequence for a single package, wherein header information and tail information are injected into the signal during the first package; then, the payload data in the packet is compressed, and a second package is performed after the compression is completed, wherein the second package is to update the first package information, update the header payload length information, add the mean value information of the entire data segment, the space occupied by the compressed single data, and the payload data CRC check information; finally, the second packaged data packet is stored in a signal storage module, wherein the frame format of the data packet is the first package header, the mean value information of the entire data segment, the space occupied by the compressed single data, the payload data CRC check information, and the compressed payload data.

[0015] The method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided by the embodiment of the present application can effectively compress ocean monitoring data and reduce the data storage capacity required per unit duty time. The method has a small amount of calculation and is simple to implement. It does not require changing the hardware of existing ocean monitoring equipment. It only needs to add the software module of the lossless compression method to the existing ocean monitoring equipment, and the increase in power consumption of the ocean monitoring equipment caused by adding the software module can be ignored. The data storage module accounts for the largest proportion of power consumption in the ocean monitoring equipment. This method reduces the power consumption of the storage module by reducing the amount of data written to the storage module per unit time, which can greatly increase the working time on the basis of the unchanged battery capacity of the original ocean monitoring equipment; or on the basis of the unchanged working time, the storage capacity and battery capacity are greatly reduced, thereby reducing the size of the equipment, reducing the difficulty of deployment and recovery, and reducing the equipment cost, making the existing ocean monitoring equipment more useful and practical. The method also reduces the communication bandwidth requirements for uploading monitoring data s between the underwater main node and multiple sub-nodes, reducing the complexity and implementation difficulty of such equipment.

[0016] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, which can be implemented in accordance with the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0018] Figure 1 A schematic diagram of the existing process functions of a method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application;

[0019] Figure 2 A functional schematic diagram of a method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application;

[0020] Figure 3 A schematic diagram of a flow chart of a method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application;

[0021] Figure 4 A schematic diagram of a data packet frame format of a method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application;

[0022] Figure 5A schematic flow chart of another method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application;

[0023] Figure 6 A schematic diagram of a data reading process of a method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application;

[0024] Figure 7 A schematic diagram of simulation data of lossless compression of ocean environment noise signals in good sea conditions for a method of lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application;

[0025] Figure 8 A schematic diagram of a lossless compression simulation compression ratio of a marine environmental noise signal in a good sea condition according to a method for lossless compression of a hydroacoustic signal suitable for marine monitoring provided in an embodiment of the present application;

[0026] Fig. 9 A schematic diagram of simulation data of lossless compression of large burst signals under good sea conditions and ocean environmental noise signals of a method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application;

[0027] Fig.10 A schematic diagram of a simulation compression ratio of a burst signal lossless compression under good sea conditions and marine environmental noise, provided in an embodiment of the present application, for a method for lossless compression of underwater acoustic signals suitable for marine monitoring;

[0028] Fig.11 A schematic diagram of simulation data of lossless compression of ocean environment noise signals in severe sea conditions of a method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application;

[0029] Fig.12 A schematic diagram of a lossless compression simulation compression ratio of a noise signal in a severe sea condition marine environment provided in an embodiment of the present application for a method for lossless compression of a hydroacoustic signal suitable for marine monitoring;

[0030] Fig.13 A schematic diagram of the structure of a lossless compression device for underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application. DETAILED DESCRIPTION

[0031] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0032] Conventional data compression is mainly used in the fields of image compression and audio compression.

[0033] 1) Image compression. Image data can be compressed because there is redundancy in the data. The redundancy of image data mainly manifests itself in: spatial redundancy caused by the correlation between adjacent pixels in the image; temporal redundancy caused by the correlation between different frames in the image sequence; and spectral redundancy caused by the correlation between different color planes or spectral bands. The purpose of data compression is to reduce the number of bits required to represent the data by removing these data redundancies.

[0034] Image compression can be either lossy or lossless. Lossless compression is preferred for technical drawings, diagrams, or cartoons, because lossy compression methods, especially at low bit rates, can introduce compression artifacts. Lossless methods are also preferred for valuable content such as medical images or scanned images for archiving. Lossy methods are well suited for natural images, for example, where a small loss in the image is acceptable (sometimes imperceptible), thus significantly reducing the number of bits.

[0035] Classic video compression algorithms have gradually formed a series of international standard systems, such as the H.26x series of recommendations, the H.320 series of recommendations, and the MPEG series of recommendations.

[0036] The basic principle of lossless compression is that the same color information only needs to be saved once. The software that compresses the image first determines which areas of the image are the same and which are different. An image that includes repeated data (such as a blue sky) can be compressed, and only the starting and ending points of the blue sky need to be recorded. However, there may be different shades of blue, and the sky may sometimes be obscured by trees, mountains, or other objects, which need to be recorded separately. In essence, lossless compression methods can remove some of the duplicate data and greatly reduce the size of the image to be saved on disk. However, lossless compression methods do not reduce the amount of memory used by the image because when the image is read from disk, the software fills in the missing pixels with the appropriate color information. If you want to reduce the amount of memory used by the image, you must use lossy compression methods.

[0037] The advantage of lossless compression method is that it can preserve the image quality better, but the compression rate of this method is relatively low.

[0038] 2) Audio compression. Audio compression technology refers to the use of appropriate digital signal processing technology on the original digital audio signal stream (PCM encoding) to reduce (compress) its bit rate without losing useful information or introducing negligible loss. It is also called compression coding. It must have a corresponding inverse transformation, called decompression or decoding. After passing through a codec system, the audio signal may introduce a lot of noise and certain distortion.

[0039] If digital audio signals are transmitted directly without compression, they will occupy a huge amount of bandwidth. For example, if the sampling frequency of a two-channel digital audio is 44.1kHz and each sample value is quantized at 16 bits, the bit rate is: 2*44.1kHz*16bit=1.411Mbit / s.

[0040] Such a large bandwidth will bring many difficulties to the transmission and processing of signals, so audio compression technology must be used to process the audio data in order to effectively transmit the audio data.

[0041] Digital audio compression coding compresses the audio data signal as much as possible while ensuring that the signal does not produce auditory distortion. Digital audio compression coding is achieved by removing redundant components in the sound signal. The so-called redundant components refer to signals in the audio that cannot be perceived by the human ear. They are of no help in determining the timbre, pitch and other information of the sound.

[0042] Redundant signals include audio signals outside the human hearing range and audio signals that are masked. For example, the frequency range of sound signals that can be perceived by the human ear is 20Hz to 20KHz. Other frequencies that cannot be perceived by the human ear can be considered redundant signals. In addition, according to the physiological and psychoacoustic phenomena of human hearing, when a strong sound signal and a weak sound signal exist at the same time, the weak sound signal will be masked by the strong sound signal and cannot be heard. In this way, the weak sound signal can be regarded as a redundant signal and does not need to be transmitted.

[0043] Existing data compression methods are designed based on the characteristics of image signals and audio signals, and cannot be applied to the compression of ocean monitoring signals. However, the embodiments of the present application take the characteristics of ocean monitoring signals into consideration and design a data lossless compression method for ocean monitoring signals, thereby reducing the storage capacity and power consumption of the device, reducing the size and cost of the device, and making the ocean monitoring device more usable and practical.

[0044] The embodiment of the present application provides a data lossless compression method suitable for marine monitoring equipment, which relies on existing marine monitoring equipment and is implemented by adding a data lossless compression module to the software of the existing marine monitoring equipment.

[0045] The functional flow of the original ocean data monitoring equipment can be found in Figure 1 ,in, Figure 1 The present invention provides a method for lossless compression of underwater acoustic signals suitable for ocean monitoring. Figure 1As shown, the following steps are included: the signal is amplified, filtered, conditioned, and collected by the front end before entering the processor for packaging, and then stored in the signal storage module. When the signal is packaged, information such as payload length, timestamp, and packet sequence number are added to facilitate subsequent recovery into a data stream within a certain period of time for data analysis.

[0046] The functional flow of the ocean monitoring equipment after data compression is as follows Figure 2 As shown, Figure 2 A functional diagram of a method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application: after the signal is packaged once, the payload data in the package is compressed, and then packaged again after compression, that is, the original package information is updated and packaged (updates the payload length information, adds the mean value of the entire package data, the size of the space occupied by a single compressed data, and the payload CRC check value), and then stored in the signal storage module.

[0047] See also Figure 3 , Figure 3 A schematic diagram of a flow chart of a method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application. Figure 3 As shown, the specific steps include the following steps.

[0048] Step S302: After the ocean acoustic signal is amplified, filtered and conditioned by the front end, the signal is collected to form a data stream, and the collected signal data stream is segmented and packaged once in time sequence, wherein header information and tail information are injected into the signal during the packaging;

[0049] Step S304: compress the payload data in the packet, and perform secondary packaging after the compression is completed, wherein the secondary packaging is to update the primary packaging information, update the payload length information of the packet header, add the average value information of the entire data segment to the packet header, and the space size information of the compressed single data and the CRC check information of the payload data;

[0050] Step S306: Store the second-packed data packet into the signal storage module, wherein the frame format of the data packet is the first-packed header, the mean information of the entire data segment, the space occupied by the compressed single data, the payload data CRC check information, and the compressed payload data.

[0051] It should be noted that the packet header information and packet trailer information here include payload length, timestamp, packet sequence number and other information.

[0052] In the embodiment of the present application, the hydroacoustic signal is first converted into an electrical signal and a hydroacoustic sensing signal; then the hydroacoustic sensing signal is amplified, filtered, conditioned, and collected to form a collected signal data stream.

[0053] In the embodiment of the present application, compressing the payload data in the packet includes:

[0054] Before compressing the payload data in the packet, the fixed-length payload data is packaged in chronological order, and the header information and the tail information are added;

[0055] The packaged data is compressed, and the space occupied by a single data after compression is determined by calculating the mean of the packaged data and the maximum absolute value of the deviation of the packaged data from the mean. The compressed data is the deviation of the original data from the mean of the packaged data.

[0056] In practical applications, first, before compression, the data is packaged according to a fixed length, and a header (payload length, timestamp, packet sequence number, etc.) and a tail are added; then, the entire package of data is compressed, and the space occupied by the compressed data is determined by calculating the mean of the entire package of data and the maximum absolute value of the deviation of the entire package of data relative to the mean. The compressed data is the deviation of the original data relative to the mean of the entire package of data.

[0057] Specifically, the compressed whole package of data is compressed, and the space occupied by the compressed single data is determined by calculating the mean of the whole package of data and the maximum absolute value of the deviation of the whole package of data from the mean, including:

[0058] Calculate the data mean of the packaged data;

[0059] According to the different resolutions of A / D conversion, the number of classification enumerations corresponding to the space occupied by a single data after compression is determined;

[0060] Calculate the absolute value of the difference between each data and the data mean, find the maximum value, and determine the space occupied by the compressed single data according to the maximum value;

[0061] In response to the maximum value of the space occupied by the compressed single data being less than the first preset space threshold, determining the size of the space occupied by the compressed data as the first occupied space;

[0062] In response to the maximum value of the space occupied by the compressed single data being greater than the first preset space threshold and less than the second preset space threshold, determining the size of the space occupied by the compressed data to be the second occupied space;

[0063] In response to the maximum value of the space occupied by the compressed single data being greater than the second preset space threshold and less than the third preset space threshold, determining the occupied space size after the data is compressed to be the third occupied space;

[0064] And so on, determine the size of the space occupied by the data after compression.

[0065] In practical applications, the average of the packed data is first calculated, which is recorded as Ave. For a system with a sampling resolution of 16 bits, the storage space size of Ave is 16 bits. Then, the absolute value of the difference between each data and the average is calculated to find the maximum value MaxDiff. The size of the space occupied by each data after compression is determined based on the maximum value. If the maximum value is less than 15, the space occupied by the compressed data is 5 bits (4 bits of lossless data plus 1 bit of sign bit). If the maximum value is less than 31, the space occupied by the compressed data is 6 bits (5 bits of lossless data plus 1 bit of sign bit), and so on.

[0066] Taking 16-bit AD sampling as an example, the preset space threshold and the corresponding occupied space size are divided into 9 categories, and the occupied space size ranges from 8 bits to 16 bits, a total of 9 categories.

[0067] When MaxDiff is less than 128 (i.e., the first preset space threshold), the corresponding first occupied space size is 8 bits;

[0068] When MaxDiff is greater than 128 and less than 256 (i.e., the second preset space threshold), the corresponding second occupied space size is 9 bits;

[0069] When MaxDiff is greater than 256 and less than 512 (ie, the third preset space threshold), the corresponding third occupied space size is 10 bits;

[0070] When MaxDiff is greater than 512 and less than 1024 (ie, the fourth preset space threshold), the corresponding fourth occupied space size is 11 bits;

[0071] When MaxDiff is greater than 1024 and less than 2048 (ie, the fifth preset space threshold), the corresponding fifth occupied space size is 12 bits;

[0072] When MaxDiff is greater than 2048 and less than 4096 (i.e., the sixth preset space threshold), the corresponding sixth occupied space size is 13 bits;

[0073] When MaxDiff is greater than 4096 and less than 8192 (i.e., the seventh preset space threshold), the corresponding seventh occupied space size is 14 bits;

[0074] When MaxDiff is greater than 8192 and less than 16384 (ie, the eighth preset space threshold), the corresponding eighth occupied space size is 15 bits;

[0075] When MaxDiff is greater than 16384 (ie, the ninth preset space threshold), the corresponding ninth occupied space size is 16 bits.

[0076] In the embodiment of the present application, secondary packaging is performed after the compression is completed, including:

[0077] Save the data mean and the space occupied by a single compressed data;

[0078] The deviation of each original data relative to the mean is stored in the corresponding position, wherein when the deviation is positive, the highest bit is determined to be zero, and when the deviation is negative, the highest bit is determined to be one.

[0079] In practical applications, the compressed data is packaged. First, the mean Ave is saved (occupying 16 bits of space), then the space occupied by the compressed data is saved (occupying 8 bits of space), and then the deviation of each original data relative to the mean is stored in the corresponding position (when the deviation is positive, the highest bit is 0, and when the deviation is negative, the highest bit is 1).

[0080] In the embodiment of the present application, the updating of the packet header payload length information includes:

[0081] Update the payload length information based on the original payload length and the space occupied by the compressed data.

[0082] In actual applications, for systems with a sampling resolution of 16 bits, update the payload length information of the first package (original payload length * space occupied by data after compression / 16. If it is a decimal, take the nearest integer greater than it). Store the compressed and packaged data into the storage space. The data packet frame format at this time is: the first package header, the average value of the entire package data, the space occupied by a single compressed data, the payload CRC check value, and the compressed payload data, see Figure 4 , Figure 4 A schematic diagram of a data packet frame format for a method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application.

[0083] See also Figure 5 , Figure 5 A flow chart of another method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application.

[0084] In an embodiment of the present application, the method further includes: reading the storage module data in the signal storage module, analyzing the packet header length segment, and reading the entire package of data that is compressed and packaged; decompressing the entire package of data, and unpacking it at the same time, to restore the data stream corresponding to the time period of the read signal. Figure 6 , Figure 6A schematic diagram of the data reading process of a method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application.

[0085] In actual applications, the compressed data recovery process is as follows: read the storage module data, analyze the packet header length segment, read the compressed entire packet data, decompress the data and unpack it to restore it into a data stream within a certain period of time.

[0086] The compression method is simple and can be implemented on common platforms of ocean monitoring equipment such as single chip microcomputer, DSP, FPGA, etc.

[0087] Specifically, the decompressing the entire package of data includes: reading the entire package of data; and restoring the original data according to the mean and the compressed data, wherein the original data is obtained based on the mean and the compressed data of the entire package of data.

[0088] In practical applications, the data of marine monitoring equipment needs to be analyzed after recovery. The data decompression method is as follows: 1) read the entire package of data; 2) restore the original data based on the mean and compressed data. The specific method is original data = mean plus or minus compressed data (if the high bit of compressed data is 0, add, if it is 1, subtract).

[0089] For the ocean environment noise in good sea conditions, the signal entering the circuit input terminal through the hydroacoustic sensor is no more than 10us. According to the conventional 500-fold conditioning and amplification and 5V AD acquisition dynamic range, the signal input to the AD terminal is no more than 5mV. Through simulation, the data compression ratio is shown in Figure 7 and Figure 8 .in, Figure 7 A schematic diagram of simulation data of lossless compression of ocean environment noise signals in good sea conditions for a method of lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application; Figure 8 A schematic diagram of the simulation compression ratio of lossless compression of marine environmental noise signals in good sea conditions, according to a method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application.

[0090] For burst signals (significant signal-to-noise ratio in the time domain), the compression ratio is shown in Fig. 9 and Fig.10 ,in, Fig. 9 A schematic diagram of simulation data of lossless compression of burst signals under good sea conditions and ocean environmental noise signals of a method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application; Fig.10 A schematic diagram of the simulation compression ratio of lossless compression of burst signals under good sea conditions and marine environmental noise for a method of lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application.

[0091] For severe marine environment, the marine environmental noise source level increases by 10 times, and the compressed ratio is shown in Fig.11 and Fig.12 ,in, Fig.11 A schematic diagram of simulation data of lossless compression of ocean environment noise signals in severe sea conditions of a method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application; Fig.12 A schematic diagram of the simulation compression ratio of lossless compression of marine environment noise signals in severe sea conditions, according to a method for lossless compression of underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application.

[0092] The following conclusions can be drawn from the simulation analysis:

[0093] Under good sea conditions, data storage capacity or communication throughput is reduced to less than 50% of the original data; under sudden data conditions, data storage capacity or communication throughput is reduced to less than 70% of the original data; under severe sea conditions, data storage capacity or communication throughput is reduced to less than 70% of the original data. For marine monitoring equipment, it is generally located at a deeper position and is not greatly affected by severe sea conditions. And the probability of sudden data in the ocean is very small.

[0094] Therefore, this method achieves the effect of significantly reducing the data storage capacity or communication throughput required by ocean monitoring equipment.

[0095] The present application provides a data lossless compression method suitable for ocean monitoring signals. The method can effectively compress ocean monitoring data and is simple to implement. It does not require improvement of the hardware complexity of existing ocean monitoring equipment, and the increase in power consumption of the ocean monitoring equipment can be ignored.

[0096] After the existing ocean monitoring equipment adds this data lossless compression method to the software module, the data storage capacity required per unit time can be greatly reduced. In ocean monitoring equipment, the data storage module accounts for the largest proportion of power consumption. Therefore, using this method can greatly increase the working time of the original ocean monitoring equipment; or, on the basis of the working time remaining unchanged, greatly reduce the storage capacity and battery capacity, thereby reducing the size of the equipment and reducing the difficulty of deployment and recovery, while reducing the equipment cost, making the existing ocean monitoring equipment more useful and practical.

[0097] Corresponding to the above method embodiment, this specification also provides an embodiment of a lossless compression device for underwater acoustic signals suitable for ocean monitoring, Fig.13 This is a schematic diagram of a structure of a lossless compression device for underwater acoustic signals suitable for ocean monitoring provided in an embodiment of the present application. Fig.13 As shown, the device comprises:

[0098] The primary packaging module 1302 is configured to collect the ocean hydroacoustic signal after front-end amplification, filtering and conditioning, to form a data stream, and to perform primary packaging on the collected signal data stream in time sequence, wherein header information and tail information are injected into the signal during the primary packaging;

[0099] The secondary packaging module 1304 is configured to compress the payload data in the packet, and perform secondary packaging after the compression is completed, wherein the secondary packaging is to update the primary packaging information, update the payload length information of the packet header, add the average value information of the entire data segment to the packet header, and the space size information of the compressed single data and the CRC check information of the payload data;

[0100] The storage module 1306 is configured to store the second-packaged data packet into the signal storage module, wherein the frame format of the data packet is the first-packaged header, the mean information of the entire data segment, the space size information of the compressed single data, the payload data CRC check information, and the compressed payload data.

[0101] In an optional embodiment, the secondary packaging module 1304 is further configured to:

[0102] Before compressing the payload data in the packet, the fixed-length payload data is packaged in chronological order, and the header information and the tail information are added;

[0103] The packaged data is compressed, and the space occupied by a single data after compression is determined by calculating the mean of the packaged data and the maximum absolute value of the deviation of the packaged data from the mean. The compressed data is the deviation of the original data from the mean of the packaged data.

[0104] In an optional embodiment, the secondary packaging module 1304 is further configured to:

[0105] Calculate the data mean of the packaged data;

[0106] According to the different resolutions of A / D conversion, the number of classification enumerations corresponding to the space occupied by a single data after compression is determined;

[0107] Calculate the absolute value of the difference between each data and the data mean, find the maximum value, and determine the space occupied by the compressed single data according to the maximum value;

[0108] In response to the maximum value of the space occupied by the compressed single data being less than the first preset space threshold, determining the size of the space occupied by the compressed data as the first occupied space;

[0109] In response to the maximum value of the space occupied by the compressed single data being greater than the first preset space threshold and less than the second preset space threshold, determining the size of the space occupied by the compressed data to be the second occupied space;

[0110] In response to the maximum value of the space occupied by the compressed single data being greater than the second preset space threshold and less than the third preset space threshold, determining the occupied space size after the data is compressed to be the third occupied space;

[0111] And so on, determine the space occupied by the compressed data.

[0112] In an optional embodiment, the secondary packaging module 1304 is further configured to:

[0113] Save the average value of the entire data package, the space occupied by a single compressed data, and the payload CRC check value;

[0114] The deviation of each original data relative to the mean of the whole package data is stored in the corresponding position, wherein when the deviation is positive, the highest bit is determined to be zero, and when the deviation is negative, the highest bit is determined to be one.

[0115] In an optional embodiment, the secondary packaging module 1304 is further configured to:

[0116] Update the payload length information based on the original payload length and the space occupied by the compressed data.

[0117] In an optional embodiment, the device further includes:

[0118] The reading module 1308 is configured to read the storage module data in the signal storage module, analyze the packet header length segment, and read the compressed and packaged whole packet data;

[0119] The depacketization module 1310 is configured to decompress the entire packet of data and depacketize the data to restore the data stream corresponding to the time period of the read signal.

[0120] In an optional embodiment, the unpacking module 1310 is further configured to:

[0121] Read the entire packet of data;

[0122] The original data is restored according to the mean value and the compressed data, wherein the original data is obtained based on the mean value and the compressed data.

[0123] The present application provides a data lossless compression device suitable for ocean monitoring signals. The device can effectively compress ocean monitoring data and is simple to implement. It does not require improvement of the hardware complexity of existing ocean monitoring equipment, and the increase in power consumption of the ocean monitoring equipment can be ignored.

[0124] After the existing ocean monitoring equipment adds the data lossless compression device to the software module, the data storage capacity required per unit time can be greatly reduced. In ocean monitoring equipment, the data storage module accounts for the largest proportion of power consumption. Therefore, the use of this device can greatly increase the working time of the original ocean monitoring equipment on the basis of the unchanged battery capacity; or on the basis of the unchanged working time, the storage capacity and battery capacity can be greatly reduced, thereby reducing the size of the equipment and reducing the difficulty of deployment and recovery, while reducing the equipment cost, making the existing ocean monitoring equipment more useful and practical.

[0125] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the lossless compression device of underwater acoustic signals suitable for ocean monitoring, since it is basically similar to the embodiment of the lossless compression method of underwater acoustic signals suitable for ocean monitoring, the description is relatively simple, and the relevant parts can be referred to the partial description of the embodiment of the lossless compression method of underwater acoustic signals suitable for ocean monitoring.

[0126] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0127] It should be noted that the above is a description of a specific embodiment of the present specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the embodiments of the present specification.

[0128] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0129] The preferred embodiments of this specification disclosed above are only used to help explain this specification. The optional embodiments do not describe all the details in detail, nor do they limit the invention to only the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of the embodiments of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the embodiments of this specification, so that technicians in the relevant technical field can well understand and use this specification. This specification is only limited by the claims and their full scope and equivalents.

Claims

1. A method for lossless compression of underwater acoustic signals suitable for ocean monitoring, characterized in that: include: After the ocean acoustic signal is amplified, filtered and conditioned at the front end, the signal is collected to form a data stream, and the collected signal data stream is segmented and packaged once in chronological order, wherein header information and tail information are injected into the signal during the packaging; Compress the payload data in the packet, and perform secondary packaging after the compression is completed, wherein the secondary packaging is to update the primary packaging information, update the payload length information of the packet header, add the mean value information of the entire data segment to the packet header, as well as the space size information of the compressed single data and the CRC check information of the payload data; The data packet after secondary packaging is stored in the signal storage module, wherein the frame format of the data packet is the packet header of the first packaging, the mean information of the entire data segment, the space size information of the compressed single data, the payload data CRC check information, and the compressed payload data.

2. The method according to claim 1, characterized in that The compressing the payload data in the packet includes: Before compressing the payload data in the packet, the fixed-length payload data is packaged in chronological order, and the header information and the tail information are added; The packaged data is compressed, and the space occupied by a single data after compression is determined by calculating the mean of the packaged data and the maximum absolute value of the deviation of the packaged data from the mean. The compressed data is the deviation of the original data from the mean of the packaged data.

3. The method according to claim 2, characterized in that The step of compressing the entire package of data after packaging and determining the space occupied by the compressed single data by calculating the mean of the entire package of data and the maximum absolute value of the deviation of the entire package of data from the mean includes: Calculate the data mean of the packaged data; According to the different resolutions of A / D conversion, the number of classification enumerations corresponding to the space occupied by a single data after compression is determined; Calculate the absolute value of the difference between each data and the data mean, find the maximum value, and determine the space occupied by the compressed single data according to the maximum value; In response to the maximum value of the space occupied by the compressed single data being less than the first preset space threshold, determining the size of the space occupied by the compressed data as the first occupied space; In response to the maximum value of the space occupied by the compressed single data being greater than the first preset space threshold and less than the second preset space threshold, determining the size of the space occupied by the compressed data to be the second occupied space; In response to the maximum value of the space occupied by the compressed single data being greater than the second preset space threshold and less than the third preset space threshold, determining the occupied space size after the data is compressed to be the third occupied space; And so on, determine the space occupied by the compressed data.

4. The method according to claim 1, characterized in that: After the compression is completed, secondary packaging is performed, including: Save the average value of the entire data package, the space occupied by a single compressed data, and the payload CRC check value; The deviation of each original data relative to the mean of the whole package data is stored in the corresponding position, wherein when the deviation is positive, the highest bit is determined to be zero, and when the deviation is negative, the highest bit is determined to be one.

5. The method according to claim 1, characterized in that The updated packet header payload length information includes: Update the payload length information based on the original payload length and the space occupied by a single compressed data.

6. The method according to claim 1, characterized in that The method further comprises: Read the storage module data in the signal storage module, analyze the packet header length segment, and read the compressed whole packet data; The entire packet of data is decompressed and unpacked at the same time to restore the acquisition signal data stream of the corresponding time period.

7. The method according to claim 6, characterized in that The decompressing the entire packet of data includes: Read the entire packet of data; The original data is restored according to the mean of the whole package data and the compressed data, wherein the original data is obtained based on the mean of the whole package data and the compressed data.

8. A lossless compression device for underwater acoustic signals suitable for ocean monitoring, characterized in that: include: The primary packaging module is configured to collect the ocean hydroacoustic signal to form a data stream after the front-end amplification, filtering and conditioning, and to perform a primary packaging on the collected signal data stream in segments in time sequence, wherein header information and tail information are injected into the signal during the primary packaging; The secondary packaging module is configured to compress the payload data in the packet and perform secondary packaging after the compression is completed, wherein the secondary packaging is to update the primary packaging information, update the payload length information of the packet header, add the mean value information of the entire data segment to the packet header, as well as the space size information of the compressed single data and the CRC check information of the payload data; The storage module is configured to store the data packet after secondary packaging into the signal storage module, wherein the frame format of the data packet is the packet header of the first packaging, the mean information of the entire data segment, the space size information of the compressed single data, the payload data CRC check information, and the compressed payload data.

9. The device according to claim 8, characterized in that The device further comprises: A reading module is configured to read the storage module data in the signal storage module, analyze the packet header length segment, and read the compressed and packaged whole packet data; The depacketizing module is configured to decompress the entire packet of data and simultaneously depacketize the data to restore the data stream corresponding to the time period of the read signal.

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