An underwater acoustic positioning adaptive smoothing filtering method and system

Abstract

The application provides a kind of underwater acoustic positioning adaptive smoothing filtering method and system, the method comprises: according to the current and last time's solution result, the speed component of target current position is calculated;The predicted value of the next position of target is calculated;The orientation and distance positioning result of the next position of target is obtained;If the deviation between the obtained positioning result and the predicted value exceeds the set threshold, the predicted value is used as the solution result;Otherwise, the obtained positioning result is used as the solution result;According to the variance of the solution result stored in history, the speed component of the target after updating positioning is calculated;The above steps are repeatedly executed to obtain the next solution result;If no positioning result is obtained, the predicted value is used as the solution result, and when the number of times of using the predicted value exceeds the set number threshold, the solution result is no longer output.The advantage of the application is that the adaptive adjustment coefficient can better adaptively filter the solution result to obtain a more smooth solution result.

Description

Technical Field

[0001] This application belongs to the field of cooperative beacon positioning technology based on underwater acoustics, specifically relating to an adaptive smoothing filtering method and system for underwater acoustic positioning. Background Technology

[0002] In radar data processing, the essence of a tracking filter is to predict the future trajectory of a target using known points, and then correct the predicted value with actual radar measurements to estimate the target's current position. Through this processing, random errors introduced during measurement can be effectively suppressed, the target's position and related motion parameters can be accurately estimated, and a stable target trajectory can be formed. From an implementation perspective, a tracking filter can be considered a type of smoothing filter, with the ultimate goal of smoothing the target trajectory.

[0003] In recent years, an increasing number of studies have applied smoothing filtering methods to the field of underwater acoustic positioning. In underwater acoustic positioning, especially in shallow sea environments, the complex underwater acoustic channels cause the propagation of acoustic signals to be subject to greater multipath response interference than in air, making underwater acoustic positioning technology more difficult to implement. Smoothing filtering, as a technique that can make positioning results smoother and more stable, has received more research and application.

[0004] Typically, a smoothing filter, as a type of filter that corrects and smooths the current detection value, does not impose many restrictions on deviation values. When a deviation value appears in the detection result, the traditional smoothing filter algorithm will correct it. Although the deviation value can also be corrected under slow motion, the deviation component will have a significant impact on subsequent filtering. Summary of the Invention

[0005] The purpose of this application is to overcome the shortcomings of existing smoothing filtering methods for low-speed moving targets, which do not consider the handling of outliers.

[0006] To achieve the above objectives, this application proposes an adaptive smoothing filtering method for underwater acoustic positioning, comprising:

[0007] Step S1: Based on the current and previous solution results, calculate the velocity components in the x and y directions of the target's current position in the Cartesian coordinate system;

[0008] Step S2: Calculate the next predicted position of the target based on the velocity components in the x and y directions of the current position in the Cartesian coordinate system;

[0009] Step S3: Obtain the target's next location, orientation, and distance, and convert it into two-dimensional coordinates;

[0010] If the deviation between the obtained positioning result and the predicted value exceeds a set threshold, the predicted value is used as the solution result; otherwise, the obtained positioning result is used as the solution result. The velocity component of the target after positioning is calculated based on the variance of the historically stored solution results. If the number of times the predicted value is used is greater than or equal to 1, the number of times the predicted value is used is reduced by 1. The solution result is stored in the historical solution storage array, and the first data in the historical solution storage array is deleted. The above steps are repeated to obtain the next solution result.

[0011] If no positioning result is obtained, the predicted value will be used as the solution result, and the number of times the predicted value is used will be incremented by 1. When the number of times the predicted value is used exceeds the set threshold, it is assumed that the positioning target is no longer in the water, and no solution result will be output.

[0012] As an improvement to the above method, it also includes: detecting the number of solution results in the historical solution storage array, and if the number reaches a set threshold, outputting the solution results.

[0013] As an improvement to the above method, the velocity components in the x and y directions of the target's current Cartesian coordinate system are calculated in step S1 and expressed as:

[0014] ;

[0015] in, and These are the velocity components in the x and y directions of the target's current Cartesian coordinate system, respectively. and These are the x and y coordinates of the target's current position, respectively. and These are the x and y coordinates of the target's previous position, respectively.

[0016] As an improvement to the above method, the next predicted position value of the target in step S2 is calculated as follows:

[0017] ;

[0018] in, and These are the predicted positions of the target for the next time.

[0019] As an improvement to the above method, in step S3, the positioning results of the next orientation and distance are obtained and converted into two-dimensional coordinates, represented as follows:

[0020] ;

[0021] in, and The two-dimensional coordinates of the transformed target; The distance to the target's next position; The direction of the target's next position.

[0022] As an improvement to the above method, step S3, which calculates and updates the velocity component of the target after positioning based on the variance of the historically stored solution results, includes:

[0023] Calculate the variance of the x and y coordinates of the solution results that are a forward number of steps from the current solution result. The variance of the x and y coordinates of the solution results obtained by setting a forward number of iterations from the previous solution result. ;

[0024] Calculate the filtering in the x and y directions. coefficient and ;

[0025] ;

[0026] The velocity update coefficients in the x and y directions are calculated using the optimal selection method. and ;

[0027] ;

[0028] Calculate the target's next x and y coordinates. and ;

[0029] ;

[0030] in, and These are the x and y coordinates of the target's current position, respectively.

[0031] Update the velocity components of the positioning target in the two-dimensional Cartesian coordinate system based on the calculated velocity update coefficient. and :

[0032] ;

[0033] Where T represents the duration of a work cycle.

[0034] This application also provides an underwater acoustic positioning adaptive smoothing filter system, implemented based on the above method, the system comprising:

[0035] The module for calculating the velocity components at the current position is used to calculate the velocity components in the x and y directions of the target's current position in the Cartesian coordinate system based on the current and previous calculation results.

[0036] The module for calculating the next position prediction value is used to calculate the next position prediction value of the target based on the velocity components in the x and y directions of the current position in the Cartesian coordinate system.

[0037] The module for obtaining the next position calculation result is used to obtain the target's next position, including its azimuth and distance, and convert it into two-dimensional coordinates. If the deviation between the obtained positioning result and the predicted value exceeds a set threshold, the predicted value is used as the solution result; otherwise, the obtained positioning result is used as the solution result. The module calculates and updates the target's velocity component based on the variance of the historically stored solution results. If the number of times the predicted value is used is greater than or equal to 1, the number of times the predicted value is used is reduced by 1. The solution result is stored in the historical solution storage array, and the first data in the historical solution storage array is deleted.

[0038] If no positioning result is obtained, the predicted value will be used as the solution result, and the number of times the predicted value is used will be incremented by 1. When the number of times the predicted value is used exceeds the set threshold, it is assumed that the positioning target is no longer in the water, and no solution result will be output.

[0039] Compared with existing technologies, the advantages of this application are:

[0040] 1. The method of the present invention uses the length of the historical solution storage array to determine the solution status of the underwater acoustic positioning beacon. The solution result can only be output after the storage meets a certain length, thus avoiding the false detection phenomenon that may occur when solving multiple underwater acoustic positioning beacons.

[0041] 2. The method of this invention is based on the assumption that "the underwater acoustic positioning beacon moves slowly underwater." Under this assumption, the continuous solution results of the underwater acoustic positioning beacon should be a continuous array with small variance. This invention, by statistically analyzing the historical variance and the variance between the current solution result and the historical solution results, adaptively adjusts the changes in the coefficients, which can better adaptively filter the solution results and obtain smoother solution results.

[0042] 3. The method of the present invention can predict the current location of the underwater acoustic beacon when the call fails, that is, when the underwater acoustic beacon does not respond. The number of predictions can be set by the user. However, considering the possibility that the underwater acoustic beacon may emerge from the water, it is generally not recommended to set too many predictions.

[0043] 4. The filtering method of the present invention has the characteristics of strong stability and simple calculation. Attached Figure Description

[0044] Figure 1 The flowchart shown is for the underwater acoustic positioning adaptive smoothing filter method.

[0045] Figure 2 The image shows a comparison of the azimuth and distance of the underwater acoustic positioning beacon before and after filtering. Detailed Implementation

[0046] The technical solution of this application will be described in detail below with reference to the accompanying drawings.

[0047] This application utilizes the characteristic that the position of a low-speed moving target (speed not exceeding 4 knots is considered low-speed movement) does not change abruptly within a continuous time period, and proposes an adaptive smoothing filtering method for underwater acoustic positioning. Based on the position change constraint, smoothing filtering is performed, and on the basis of smoothing filtering, occasional outliers are eliminated, resulting in a more stable and smooth positioning result.

[0048] Example 1

[0049] like Figure 1 As shown, the underwater acoustic positioning adaptive smoothing filtering method proposed in this invention includes:

[0050] Step 1: Create a historical solution record array , The array length is k; a record is created for the number of times the predicted value is directly used. ;

[0051] Step 2: Check the length of the historical solution storage array. If it reaches the set length (array length k), it is considered to have a certain stable state and is not due to occasional false detection. Then the solution result is output. Otherwise, it will continue to store until the storage length reaches the set length.

[0052] Step 3: Check the current solution result. If the solution result exceeds the boundary value, delete the first and second characters of the historical solution storage array and reduce the length of the historical solution storage array by 1. If it does not exceed the boundary value, transfer the current solution result to Step 4 for filtering calculation.

[0053] Step 4: Calculate the variance in the x and y directions in the rectangular coordinate system based on the historically stored settlement results. ;

[0054] Based on the results of the kth and (k-1)th calculations, calculate the velocity in the Cartesian coordinate system direction in the kth calculation.

[0055] ;

[0056] Based on the calculated velocities in each direction, the predicted rectangular coordinate position for the (k+1)th iteration is given.

[0057] ;

[0058] The location result of the (k+1)th time with direction and distance. Convert to two-dimensional rectangular coordinates;

[0059] ;

[0060] Check whether the positioning result of the (k+1)th iteration deviates too much from the solution result of the kth iteration. If the deviation of the solution result is large, then the prediction result is considered to be the solution result. If the result remains unchanged, the obtained positioning result will be used as the solution result.

[0061] Calculate the variance of the k solutions, including the (k+1)th solution. ;

[0062] Calculate the filter coefficient;

[0063] ;

[0064] Calculate the speed update coefficient using the optimal selection method. ;

[0065] ;

[0066] According to calculation The filtered value is derived from the coefficients, predicted values, and calculated values.

[0067] ;

[0068] According to calculation The coefficients are used to update the velocity components of the positioning target in the two-dimensional Cartesian coordinate system; the calculated velocity components can provide support for the next position prediction value.

[0069] ;

[0070] Where T represents the duration of a work cycle.

[0071] If the solution is output normally according to the smoothing formula, the solution status is considered normal. If the value is greater than or equal to 1, then subtract 1 from it;

[0072] The filtered result is stored in the historical solution storage array, and the first element of the historical solution storage array is deleted to ensure that its length is the set length.

[0073] Convert coordinates in a two-dimensional rectangular coordinate system into azimuth and distance, and output the smoothed and filtered result.

[0074] Check if the filtered result is abnormal. If no abnormality is found, output the filtered result. The abnormality of the filtered result is determined based on the set threshold.

[0075] If the positioning result of the (k+1)th step is not detected, but the filtering step is still entered, it is considered that the frame is missed and the predicted value is output as the result. The value is incremented by 1 when If the value exceeds the specified value, it is assumed that the target is no longer in the water, and the solution will no longer be output and the first record of the historical solution storage array will be deleted.

[0076] The method of the present invention is then tested. In the experiment, the underwater acoustic positioning beacon is launched into the water from a slowly moving small boat and slowly moves from a distance of 200m to a distance of 600m to locate the position of the underwater acoustic positioning beacon in the water.

[0077] The method of the present invention is based on the following assumption: the movement of an individual carrying an underwater acoustic positioning beacon is low speed.

[0078] The comparison images of the azimuth and distance of the underwater acoustic positioning beacon before and after filtering are shown below. Figure 2 As shown, there are some missed detections and outliers in the initial solution. Although they are few, they still affect the stability of the overall positioning. This problem is solved after smoothing filtering.

[0079] Example 2

[0080] This application also provides an underwater acoustic positioning adaptive smoothing filter system, implemented based on the above method, the system comprising:

[0081] The module for calculating the velocity components at the current position is used to calculate the velocity components in the x and y directions of the target's current position in the Cartesian coordinate system based on the current and previous calculation results.

[0082] The module for calculating the next position prediction value is used to calculate the next position prediction value of the target based on the velocity components in the x and y directions of the current position in the Cartesian coordinate system.

[0083] The module for obtaining the next position calculation result is used to obtain the target's next position, including its azimuth and distance, and convert it into two-dimensional coordinates. If the deviation between the obtained positioning result and the predicted value exceeds a set threshold, the predicted value is used as the solution result; otherwise, the obtained positioning result is used as the solution result. The module calculates and updates the target's velocity component based on the variance of the historically stored solution results. If the number of times the predicted value is used is greater than or equal to 1, the number of times the predicted value is used is reduced by 1. The solution result is stored in the historical solution storage array, and the first data in the historical solution storage array is deleted.

[0084] If no positioning result is obtained, the predicted value will be used as the solution result, and the number of times the predicted value is used will be incremented by 1. When the number of times the predicted value is used exceeds the set threshold, it is assumed that the positioning target is no longer in the water, and no solution result will be output.

[0085] This application may also provide a computer device, including: at least one processor, memory, at least one network interface, and a user interface. The various components in this device are coupled together via a bus system. It is understood that the bus system is used to implement communication between these components. In addition to a data bus, the bus system also includes a power bus, a control bus, and a status signal bus.

[0086] The user interface can include a display, keyboard, or clicking device. Examples include a mouse, trackball, touchpad, or touchscreen.

[0087] It is understood that the memory in the embodiments disclosed in this application may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory may be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memories described herein are intended to include, but are not limited to, these and any other suitable types of memory.

[0088] In some implementations, the memory stores elements such as executable modules or data structures, or subsets thereof, or extended sets thereof: operating systems and applications.

[0089] The operating system includes various system programs, such as the framework layer, core library layer, and driver layer, used to implement various basic business functions and handle hardware-based tasks. The application programs include various applications, such as media players and browsers, used to implement various application functions. Programs implementing the methods of the embodiments of this disclosure can be included in the application programs.

[0090] In the above embodiments, the processor can also invoke programs or instructions stored in memory, specifically programs or instructions stored in an application program, for the following purposes:

[0091] Follow the steps described above.

[0092] The above methods can be applied to or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above methods can be completed by integrated logic circuits in the processor's hardware or by software instructions. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic diagrams disclosed above. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the disclosed methods can be directly implemented by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above methods.

[0093] It is understood that the embodiments described in this application can be implemented using hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described in this application, or combinations thereof.

[0094] For software implementation, the technology of this application can be implemented by executing the functional modules (e.g., procedures, functions, etc.) of this application. The software code can be stored in memory and executed by a processor. The memory can be implemented in the processor or outside the processor.

[0095] This application may also provide a non-volatile storage medium for storing a computer program. When the computer program is executed by a processor, it can implement the steps in the above method embodiments.

[0096] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it. Although this application has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent substitutions to the technical solutions of this application do not depart from the spirit and scope of the technical solutions of this application, and should all be covered within the scope of the claims of this application.

Claims

1. A method for underwater acoustic positioning adaptive smoothing filtering, comprising: Step S1: calculating the velocity components of the target in the x and y directions of the rectangular coordinate system according to the current and previous calculation results; Step S2: calculating the next position prediction value of the target according to the velocity components of the target in the x and y directions of the rectangular coordinate system; Step S3: obtaining the positioning results of the next position of the target in the azimuth and distance, and converting them into two-dimensional coordinates; if the deviation between the obtained positioning results and the prediction value exceeds a set threshold, using the prediction value as the calculation result; otherwise, using the obtained positioning results as the calculation result; calculating the velocity components of the target after the positioning update according to the variance of the historical calculation results; if the number of times of using the prediction value is greater than or equal to 1, reducing the number of times of using the prediction value by 1; storing the calculation result in a historical calculation storage array, and deleting the first data in the historical calculation storage array; repeating the above steps to obtain the next calculation result; if the positioning results are not obtained, using the prediction value as the calculation result, and increasing the number of times of using the prediction value by 1; when the number of times of using the prediction value exceeds a set number threshold, considering that the positioning target is not in the water, and no longer outputting the calculation result.

2. The method according to claim 1, wherein, Further comprising: detecting the number of calculation results in the historical calculation storage array; if the number reaches a set number threshold, outputting the calculation result.

3. The adaptive smoothing filter method for underwater acoustic positioning according to claim 1, characterized in that, In the step S1, the velocity components of the target in the x and y directions of the rectangular coordinate system are calculated and represented as: ； wherein, and are the velocity components in the x, y directions of the current Cartesian coordinate system of the target, respectively; and are the x and y coordinates of the current position of the target, respectively; and are the x and y coordinates of the last position of the target, respectively.

4. The method of claim 3, wherein, In the step S2, the next position prediction value of the target is calculated and represented as: ； wherein, and are the next position prediction values of the target, respectively.

5. The adaptive smoothing filter method for underwater acoustic positioning according to claim 1, wherein, In the step S3, the positioning results of the next position of the target in the azimuth and distance are obtained, and converted into two-dimensional coordinates, and represented as: ； wherein, and are coordinate values in the x and y directions of the target next position; is the distance of the target next position; is the bearing of the target next position.

6. The method of claim 1, wherein, In the step S3, the velocity components of the target after the positioning update are calculated according to the variance of the historical calculation results, comprising: calculating the variance of the x and y coordinates of the forward number of solutions set forward from the current solution , and the variance of the x and y coordinates of the forward number of solutions set forward from the previous solution ; The filtered x and y direction coefficients are calculated as and ;​ ； The velocity update coefficients in x and y directions are calculated according to the optimal selection method and ; ； calculating the target next position x and y direction coordinate values and ; ； wherein, and are the x and y coordinates of the current position of the target, respectively. According to the calculated speed update coefficient, the speed component in the positioning target two-dimensional rectangular coordinate system is updated and The value of and : ； wherein T represents the length of a working cycle.

7. A system for underwater acoustic positioning adaptive smoothing filtering, realized based on the method according to any one of claims 1-6, characterized in that, The system comprises: a module for calculating the velocity components of the current position, configured to calculate the velocity components of the target in the x and y directions of the rectangular coordinate system according to the current and previous calculation results; a module for calculating the next position prediction value, configured to calculate the next position prediction value of the target according to the velocity components of the target in the x and y directions of the rectangular coordinate system; and a module for obtaining the next position calculation result, configured to obtain the positioning results of the next position of the target in the azimuth and distance, and convert them into two-dimensional coordinates; if the deviation between the obtained positioning results and the prediction value exceeds a set threshold, using the prediction value as the calculation result; otherwise, using the obtained positioning results as the calculation result; calculating the velocity components of the target after the positioning update according to the variance of the historical calculation results; if the number of times of using the prediction value is greater than or equal to 1, reducing the number of times of using the prediction value by 1; storing the calculation result in a historical calculation storage array, and deleting the first data in the historical calculation storage array; if the positioning results are not obtained, using the prediction value as the calculation result, and increasing the number of times of using the prediction value by 1; when the number of times of using the prediction value exceeds a set number threshold, considering that the positioning target is not in the water, and no longer outputting the calculation result.

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