Method, system and device for identifying individual fish based on average frequency of broadband signal

Abstract

The application discloses a single fish recognition method, system and equipment based on a wideband signal average frequency, relates to the underwater detection technical field, and comprises the following steps: performing digital band-pass filtering on a received echo signal; performing root-mean-square envelope calculation on the filtered signal, and performing endpoint recognition to obtain multiple signal segments; dividing the signal segments, and calculating average power of the segmented signals; and performing single fish recognition based on the average power and ideal average power; and the ideal average power is average power of ideal segmented signals corresponding to an ideal transmission signal. Through the calculation of the segmented average frequency of the echo signal, the single fish echo signal and the group fish echo signal can be effectively distinguished.

Description

Technical Field

[0001] This invention relates to the field of underwater detection technology, and in particular to a method, system and device for identifying individual fish based on the average frequency of broadband signals. Background Technology

[0002] Acoustic technology plays a crucial role in underwater detection. Sound waves travel faster underwater than in air, enabling detection and communication over longer distances. Furthermore, sound waves have stronger propagation capabilities in water, penetrating plankton, sediment, and suspended matter to transmit echo signals. By analyzing the acoustic characteristics of these echo signals, single-target echoes can be distinguished from group echoes, thus achieving single-target identification. Broadband split beamforming, with its high transmission rate, high target positioning accuracy, and strong anti-interference capabilities, is widely used in single-target identification technology. Traditional single-target identification methods mainly include pulse width, amplitude, and phase deviation methods. Pulse width and amplitude criteria are significantly affected by the testing environment, making it impossible to identify single targets in harsh environments. Phase deviation, on the other hand, is affected by the time-varying phase difference of broadband signals and is only applicable to narrowband signals. Summary of the Invention

[0003] The purpose of this invention is to provide a method, system, and device for identifying individual fish based on the average frequency of broadband signals, which is less affected by environmental factors.

[0004] To achieve the above objectives, the present invention provides the following solution:

[0005] A method for identifying individual fish based on the average frequency of broadband signals, comprising:

[0006] The received echo signal is digitally bandpass filtered; the echo signal is obtained using an underwater acoustic detection system.

[0007] The root mean square envelope of the filtered signal is calculated, and endpoint identification is performed to obtain multiple signal segments.

[0008] Divide the signal into segments and calculate the average power of each segment.

[0009] Based on the average power and the ideal average power, single fish are identified; the ideal average power is the average power of the ideal segmented signal corresponding to the ideal transmitted signal.

[0010] To achieve the above objectives, the present invention also provides the following solution:

[0011] A single fish identification system based on the average frequency of broadband signals, comprising:

[0012] The filtering module is used to perform digital bandpass filtering on the received echo signal; the echo signal is obtained by an underwater acoustic detection system.

[0013] The identification module is used to calculate the envelope of the filtered signal by root mean square and to identify the endpoints to obtain multiple signal segments.

[0014] The average power calculation module is used to divide the signal into segments and calculate the average power of each segment.

[0015] The single fish identification module is used to identify a single fish based on the average power and the ideal average power; the ideal average power is the average power of the ideal segmented signal corresponding to the ideal transmitted signal.

[0016] To achieve the above objectives, the present invention also provides the following solution:

[0017] An electronic device includes a memory and a processor, the memory storing a computer program, and the processor running the computer program to enable the electronic device to perform the above-described method for identifying individual fish based on the average frequency of broadband signals.

[0018] To achieve the above objectives, the present invention also provides the following solution:

[0019] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the single fish identification method based on the average frequency of a broadband signal as described above.

[0020] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0021] This invention calculates the average frequency of segmented echo signals, which can extract the frequency characteristics of the signals for classification and identification. It can also understand the main frequency components and frequency distribution of the signals, thereby distinguishing between the echo signals of individual fish and the echo signals of groups of fish, and thus completing the identification of individual fish. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 A flowchart of the single fish identification method based on the average frequency of broadband signals provided by the present invention;

[0024] Figure 2This is a detailed flowchart of the single fish identification method based on the average frequency of broadband signals provided by the present invention;

[0025] Figure 3 This is a schematic diagram of signal segmentation;

[0026] Figure 4 This is a schematic diagram of the test system;

[0027] Figure 5 A schematic diagram for identifying signal segment endpoints;

[0028] Figure 6 This is a schematic diagram showing the average frequency of signal s1;

[0029] Figure 7 This is a schematic diagram of the average frequency of signal s2. Detailed Implementation

[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] For linear frequency modulated (LFM) signals, their frequency changes according to a certain pattern, varying linearly with time. For two identical LFM signals, the frequency changes over time before and after overlap are different. After overlap, due to the mutual influence of amplitude and phase, a new waveform will appear, and its time-domain characteristics will change. Therefore, this characteristic can be used to distinguish between the non-overlapping signal and the overlapped signal. The average frequency of a signal has wide applications in signal processing and spectrum analysis. It can not only extract the frequency characteristics of a signal and analyze its frequency distribution, but also is frequently used in frequency estimation, tracking, and locking.

[0032] Therefore, the purpose of this invention is to provide a method, system, and device for identifying individual fish based on the average frequency of broadband signals. By calculating the average frequency of the echo signal in segments, the echo signal of an individual fish can be distinguished from the echo signal of a group of fish.

[0033] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0034] Example 1

[0035] like Figure 1 and Figure 2 As shown, the single fish identification method based on the average frequency of broadband signals provided in this embodiment includes the following steps:

[0036] S1: Perform digital bandpass filtering on the received echo signal; the echo signal is obtained by an underwater acoustic detection system.

[0037] The receiver in the underwater acoustic detection system receives the echo signal sig. The received signal is obtained by digital bandpass filtering. The upper and lower boundary frequencies of the passband are f0-BW / 2 and f0+BW / 2, respectively. The passband attenuation is 3dB. The upper and lower boundary frequencies of the stopband are f0-BW / 2-5000 and f0+BW / 2+5000, respectively. f0 is the center frequency and BW is the signal bandwidth.

[0038] S2: Calculate the envelope of the filtered signal using the root mean square and identify the endpoints to obtain multiple signal segments.

[0039] The envelope of the signal sn is calculated using the root mean square (RMS) of the noise. The mean RMS of the noise is used as a threshold to identify the endpoints of the echo signal, thus obtaining the signal segment sn. j (j = 1, 2, ..., m, where m is the number of suspected signals identified).

[0040] S3: Divide the signal into segments and calculate the average power of each segment.

[0041] Calculate the power density of the signal according to the length of each segment, such as Figure 3 The power of part1, part2, ... is calculated separately, and the length of each segment signal is the same.

[0042] The power calculation formula is as follows, where Fs is the sampling frequency, N is the segmented signal length, and part i For the segmented signal, P i This corresponds to the calculated power of each segment of the signal.

[0043]

[0044] The average power of each signal segment is then calculated using the following formula:

[0045]

[0046] S4: Based on the average power and the ideal average power, perform single fish identification; the ideal average power is the average power of the ideal segmented signal corresponding to the ideal transmitted signal.

[0047] Following the above calculation process, the center frequency fc_ideal of each signal segment is calculated using the window function np sampling points, and then MN... Fij Compare with fc_ideal.

[0048] Since the transmitted signal is a linear frequency modulated (LFM) signal, the difference between the center frequencies of the two connected signal segments calculated using the np-point window function should be a constant. If the absolute value of the difference is |MNF... ij If –fc_ideal| is greater than deltaF, then the segmented signal is a group fish echo signal; otherwise, it is a single fish echo signal. The expression for deltaF is shown in formula (3), where T is the pulse width of the transmitted signal.

[0049]

[0050] Determine if the suspicious signal has been processed, i.e., check if j is less than m. If it is, return to step S3 and process sn. j+1 Calculate the average frequency of each segment of the signal; otherwise, end the calculation and prepare to process the next segment of the echo signal.

[0051] The experimental results of this invention are as follows:

[0052] Test system such as Figure 4 As shown, during the test, a Simard EK80 split-beam transducer was used with a beam opening angle of 7°, a center frequency of 200kHz, a bandwidth of 40kHz, a transmit pulse width of T = 1ms, and a sampling frequency of Fs = 2MHz. Tungsten steel spheres were used instead of live fish, with 50 target spheres. Individual fish were approximately 4m away from the transducer, and the transducer and the group of fish were submerged at the same depth, approximately 3m. Individual fish and the group of fish were fixed on vehicles A and B, respectively. By changing the distance between vehicles A and B, different relative distances between individual and group fish were simulated. The distance between the standard spheres in the group of fish was no greater than the minimum resolvable distance of the sonar, cT / 2, where c is the speed of sound in water, taken as 1500m / s.

[0053] Figure 5 These are the measured results when the distance between a single fish and a group of fish is 70cm. Figure 4 As shown, a single fish is closer to the transducer than a group of fish. Therefore Figure 5 The portion between the start and end points of the first group should be the echo signal of a single fish. The threshold calculated based on the noise from the air sample can be used to identify the endpoints of the echo signal received by the receiver, resulting in two echo signals s1 and s2 excluding the noise.

[0054] The window size np = 200 (can be adjusted according to the sampling frequency and period), and deltaF is calculated to be 4kHz using formula (3). The average frequency of the s1 signal is calculated segment by segment, as follows: Figure 6 As shown in (c), the calculated average frequency MNF i1 (i = 1, 2, ..., L) s1 / np, where L s1If the signal length of s1 is close to the center frequency of the ideal segmented signal and the absolute value of the difference is less than deltaF, then the signal segment is determined to be a single fish echo signal.

[0055] Perform segmented average frequency calculation on the s2 signal, such as... Figure 7 As shown in (c), the calculated average frequency MNF i2 (i = 1, 2, ..., L) s2 / np, where L s2 Subtracting the center frequency of the ideal segmented signal from the signal length of s2, the calculated deltaF does not meet the threshold condition, therefore this part is the echo signal of the group of fish.

[0056] Example 2

[0057] In order to implement the method corresponding to Embodiment 1 above and achieve the corresponding functions and technical effects, a single fish identification system based on the average frequency of broadband signals is provided below.

[0058] The system includes:

[0059] The filtering module is used to perform digital bandpass filtering on the received echo signal.

[0060] The identification module is used to calculate the envelope of the filtered signal by root mean square and to identify the endpoints to obtain multiple signal segments.

[0061] The average power calculation module is used to divide the signal into segments and calculate the average power of each segment.

[0062] The single fish identification module is used to identify a single fish based on the average power and the ideal average power; the ideal average power is the average power of the ideal segmented signal corresponding to the ideal transmitted signal.

[0063] Example 3

[0064] Embodiment 3 of the present invention provides an electronic device, including a memory and a processor. The memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to perform the single fish identification method based on the average frequency of broadband signals provided in Embodiment 1.

[0065] In practical applications, the aforementioned electronic devices can be servers.

[0066] In practical applications, electronic devices include: at least one processor, memory, bus, and communication interface.

[0067] The processor, communication interface, and memory communicate with each other via a communication bus.

[0068] A communication interface is used to communicate with other devices.

[0069] The processor is used to execute programs, specifically the methods described in the above embodiments.

[0070] Specifically, the program may include program code, which includes computer operation instructions.

[0071] The processor may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The electronic device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or they may be processors of different types, such as one or more CPUs and one or more ASICs.

[0072] Memory is used to store programs. Memory may include high-speed RAM, and may also include non-volatile memory, such as at least one disk drive.

[0073] Example 4

[0074] Based on the description of Embodiment 3, Embodiment 4 of the present invention provides a storage medium on which a computer program is stored. The computer program can be executed by a processor to implement the single fish identification method based on the average frequency of broadband signals of Embodiment 1.

[0075] The single fish identification system based on the average frequency of broadband signals provided in Embodiment 2 of this invention exists in various forms, including but not limited to:

[0076] (1) Mobile communication devices: These devices are characterized by their mobile communication capabilities and primarily aim to provide voice and data communication. These terminals include: smartphones (e.g., iPhones), multimedia phones, feature phones, and low-end phones, etc.

[0077] (2) Ultra-mobile personal computer devices: These devices fall under the category of personal computers, possessing computing and processing capabilities, and generally also have mobile internet access capabilities. These terminals include PDAs, MIDs, and UMPCs, such as the iPad.

[0078] (3) Portable entertainment devices: These devices can display and play multimedia content. This category includes: audio and video players (such as iPods), handheld game consoles, e-books, as well as smart toys and portable car navigation devices.

[0079] (4) Other electronic devices with data interaction functions.

[0080] Specific embodiments of the subject matter have now been described. Other embodiments are within the scope of the appended claims. In some cases, the actions described in the claims can be performed in a different order and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing can be advantageous.

[0081] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0082] For ease of description, the above apparatus is described by dividing it into various functional units. Of course, in implementing this invention, the functions of each unit can be implemented in one or more software and / or hardware components. Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0083] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0084] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0085] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0086] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0087] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0088] Computer-readable media, including both permanent and non-permanent, removable and non-removable media, can store information using any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined in this invention, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0089] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0090] This invention can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer.

[0091] Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific transactions or implement specific abstract data types. This invention can also be practiced in distributed computing environments where transactions are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0092] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0093] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for identifying a single fish based on the average frequency of a broadband signal, characterized in that, include: The received echo signal is digitally bandpass filtered; The echo signal was obtained using an underwater acoustic detection system; The envelope of the filtered signal sn is calculated using the root mean square (RMS) method. The mean RMS value of the noise from the air sampling is used as a threshold. Endpoint identification is then performed on the echo signal to obtain the signal segment sn. j j=1,2..,m, where m is the number of suspected signals identified; The signal is divided into segments, and the average power of each segment is calculated. Specifically, the power density is calculated for each segment according to its length. The power calculation formula is as follows: P i To correspond to the calculated power of each signal segment, The signal is segmented, Fs is the sampling frequency, and N is the length of each segment. The average power of each segment is then calculated. ; Based on the average power and ideal average power, single fish identification is performed; the ideal average power is the average power of the ideal segmented signal corresponding to the ideal transmitted signal; specifically, this includes selecting a window function np sampling point to calculate the center frequency fc_ideal of each signal segment, and then... Compared to fc_ideal, since the transmitted signal is a linear frequency modulated signal, the difference between the center frequencies of two consecutive signal segments calculated using the np-point window function should be a constant. If the absolute value of the difference is |MNF ij If –fc_ideal| is greater than deltaF, then the segmented signal is a group fish echo signal; otherwise, it is a single fish echo signal. The expression for deltaF is: Where T is the transmitted signal pulse width; determine if j is less than m, if so, return to step "divide the signal into segments and calculate the average power of each segment", for sn j+1 Calculate the average frequency of each segment of the signal; otherwise, end the calculation and prepare to process the next segment of the echo signal.

2. A single fish identification system based on the average frequency of broadband signals, characterized in that, include: The filtering module is used to perform digital bandpass filtering on the received echo signal; The echo signal was obtained using an underwater acoustic detection system; The identification module is used to calculate the envelope of the filtered signal sn using the root mean square (RMS) value, and to use the mean RMS value of the noise from the air sampling as a threshold to identify the endpoints of the echo signal, thus obtaining the signal segment sn. j j=1,2..,m, where m is the number of suspected signals identified; The average power calculation module is used to divide the signal into segments and calculate the average power of each segment. Specifically, it calculates the power density of the signal according to the length of each segment, using the following formula: P i To correspond to the calculated power of each signal segment, The signal is segmented, Fs is the sampling frequency, and N is the length of each segment. The average power of each segment is then calculated. ; The single fish identification module is used to identify single fish based on the average power and the ideal average power; the ideal average power is the average power of the ideal segmented signal corresponding to the ideal transmitted signal, specifically including selecting a window function np sampling points to calculate the center frequency fc_ideal of each signal segment, and then... Compared to fc_ideal, since the transmitted signal is a linear frequency modulated signal, the difference between the center frequencies of two consecutive signal segments calculated using the np-point window function should be a constant. If the absolute value of the difference is |MNF ij If –fc_ideal| is greater than deltaF, then the segmented signal is a group fish echo signal; otherwise, it is a single fish echo signal. The expression for deltaF is: Where T is the transmitted signal pulse width; determine if j is less than m, if so, return to step "divide the signal into segments and calculate the average power of each segment", for sn j+1 Calculate the average frequency of each segment of the signal; otherwise, end the calculation and prepare to process the next segment of the echo signal.

3. An electronic device, characterized in that, The device includes a memory and a processor, the memory being used to store a computer program, and the processor running the computer program to cause the electronic device to perform the single fish identification method based on the average frequency of a broadband signal as described in claim 1.

4. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the single fish identification method based on the average frequency of a broadband signal as described in claim 1.

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