CN110196425B - Passive acoustic positioning method for underwater target by mobile platform - Google Patents
Passive acoustic positioning method for underwater target by mobile platform Download PDFInfo
- Publication number
- CN110196425B CN110196425B CN201910405417.9A CN201910405417A CN110196425B CN 110196425 B CN110196425 B CN 110196425B CN 201910405417 A CN201910405417 A CN 201910405417A CN 110196425 B CN110196425 B CN 110196425B
- Authority
- CN
- China
- Prior art keywords
- mobile platform
- target
- positioning
- objective function
- current
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
- G01S15/02—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems using reflection of acoustic waves
- G01S15/06—Systems determining the position data of a target
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Acoustics & Sound (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Physics & Mathematics (AREA)
- Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)
Abstract
The invention discloses a passive acoustic positioning method of a mobile platform on an underwater target, which comprises the following steps: 1) the method comprises the steps that a mobile platform receives a noise signal radiated by an underwater target once in each moving step; wherein, one step is a set distance length; 2) calculating the sound propagation time difference between the array elements on the mobile platform at the current position according to the noise signals; 3) calculating a target function of the current position of the mobile platform by utilizing a plurality of previously calculated sound propagation time differences and the corresponding positions of the mobile platform; 4) searching and positioning the underwater target by using an optimization method for searching the minimum value of the target function to obtain a positioning estimation result of the current position of the mobile platform on the underwater target, thereby realizing high-precision passive acoustic positioning; in addition, due to the path planning using the gradient descent method, the number of positioning times required to meet the positioning accuracy requirement is the smallest of all paths.
Description
Technical Field
The invention belongs to the technical field of signal processing methods, and particularly relates to a passive acoustic positioning method of a mobile platform for an underwater target.
Background
With the rapid development of ocean and environmental development, the technologies of various Surface and Underwater mobile platforms, such as Unmanned Surface Vehicles (USVs), Unmanned Underwater Vehicles (UUVs) or Autonomous Underwater robots (AUVs), have become research hotspots in many countries with advanced ocean technologies. The USV, UUV or AUV often integrates artificial intelligence and other task controllers of advanced computing technology, integrates high technologies such as a propeller (deep submergence vehicle), a sensor, energy storage and conversion, an underwater intelligent weapon and the like, and is used in the fields of anti-submergence warfare, mine warfare, reconnaissance monitoring, logistics support and the like in military; the device can also be used in other underwater fields, such as civil fields of underwater detection, marine environment monitoring, marine surveying and mapping, marine construction and the like.
The passive acoustic positioning of an underwater target refers to a positioning method for obtaining the position of the target by receiving acoustic signals emitted by the target without actively emitting detection acoustic signals by a positioning system (positioning sonar). The passive acoustic positioning method can ensure the self concealment of the platform, and therefore, the passive acoustic positioning method has important significance for the underwater target detection field, particularly the military field.
The current passive acoustic positioning technology field of underwater targets is limited by the size of a platform, and can be divided into Long Base Line (LBL) positioning, Short Base Line (SBL) positioning and Ultra-Short base line (USBL) positioning according to different array base line sizes, wherein the base line lengths are kilometric, meter and centimeter. The length of the baseline affects the freedom of array layout.
The passive acoustic positioning of the underwater target by the mobile platform refers to the passive acoustic positioning of the underwater target by utilizing a water surface or underwater mobile platform, such as a USV, a UUV or an AUV. Due to the characteristics of the platform, the specificity of realizing the passive positioning method is determined. For these mobile platforms, the size is limited, and the number of array elements and the arrangement space for positioning are limited, so that positioning is generally realized by using a short base line or an ultra-short base line array; in addition, because the platform has mobility, continuous and multiple positioning of the target can be realized in the moving process, and therefore, the continuous and multiple positioning results can be fused by utilizing the correlation of the continuous and multiple positioning processes, so that the positioning precision is improved; meanwhile, a reasonable objective function can be utilized to plan the moving path of the platform, so that the positioning system can be converged to the positioning error requirement to be met at the highest speed.
A model of passive acoustic localization of underwater targets by a mobile platform is shown in figure 1. The acoustic positioning system on the platform adopts m (m is more than or equal to 4) array elements (which can be hydrophones, receiving transducers or acoustic sensors) to form a positioning array, and the array elements are marked as follows: s1,S2,S3,…,Sm. The moving track of the platform center is shown as a dotted line in the attached figure 1. In the terrestrial coordinate system (fixed coordinate system) (x, y, z), the position during the movement of the center of the platform is marked as O1,O2,O3,…,On(ii) a The coordinate system of the platform fixed on the platform and positioned at the center of the platform is set to be (x ', y ', z '), and the position of the target in the water is set to be P. According to a traditional passive acoustic positioning method, acoustic signals of acoustic waves radiated by a target sound source and transmitted to all receiving hydrophone (array element) channels through a water medium are acquired through multi-channel (at present, 4 channels are used at most, 6 channels are used at most) acoustic signal acquisition; measuring the sound propagation time difference (time difference for short) between the target and each array element and a reference array element by using a high-precision time difference measuring method; the position of the target in the platform coordinate system is solved by solving an algebraic equation system or by utilizing a least mean square error (LMS) algorithm, and then the position of the target in the terrestrial coordinate system is solved according to the attitude and the position of the platform.
Currently, a typical underwater short-baseline or ultra-short-baseline acoustic positioning system mainly uses a traditional 4-array element positioning method, including products produced by Sonardyne corporation and Simrad corporation in UK, and an acoustic array with a baseline length of 600mm-800mm is used, so that the positioning performance can reach 0.5% of the slant distance in a kilometer range (the slant distance represents the distance between two points which are not at the same height). The French IxSea company can achieve the precision of 0.3% of the slant distance by matching an ultra-short baseline positioning system with an inertial navigation system and utilizing an acoustic array with the baseline length of about 500 mm. However, when the target distance is long, the positioning error is large due to the small arrival time difference (or phase difference) between the array elements, and thus the target positioning cannot be performed, and only direction finding can be achieved. Therefore, some subsequent researches have been conducted to improve the accuracy or stability of the passive acoustic positioning system by increasing the number of array elements, such as 5-element and 6-element arrays.
In a conventional 4-element array, 5-element array and 6-element array positioning method, models in fig. 1 are adopted, and the number of array elements is set to be m equal to 4,5 and 6 respectively. A single positioning of the target P is achieved when the platform is moved to a certain position. These methods may utilize multiple averaging of independent positioning results to improve positioning accuracy. However, in this process, each single positioning process is regarded as an independent positioning process, correlation between continuous multiple positioning results in the platform moving process is not utilized, and the moving path of the platform is not optimized, so that improvement of precision is limited.
Therefore, how to further improve the positioning accuracy of the short baseline or the ultra-short baseline still remains a concern.
For an underwater mobile platform, because the results of continuous multiple positioning in the moving process of the platform have correlation, how to utilize the correlation makes a positioning system quickly converge to a required positioning error in the moving and positioning process is the key for improving the positioning accuracy. Therefore, the invention provides a high-precision passive positioning algorithm of the mobile platform and a track optimization algorithm of the platform movement, which can enable the mobile platform to realize high-precision positioning of the target, quickly converge to the required positioning error and meet the positioning precision requirement. Optimization of the trajectory also means that the mobile platform can be quickly locked to a target position, consume less energy, and have greater concealment.
Disclosure of Invention
Aiming at the problem of passive acoustic positioning of a moving platform on an underwater target, the invention aims to provide a high-precision positioning method capable of rapidly converging to a required positioning error. The method of the invention comprises two contents: firstly, a new objective function is provided to realize high-precision positioning by utilizing the correlation of continuous multiple positioning results in the moving process of a platform; secondly, a method for enabling a positioning system on a mobile platform to quickly converge to a required positioning error through the optimization of the moving track of the platform to meet the requirement of positioning accuracy is provided.
In order to achieve the purpose, the invention adopts the following technical scheme:
in the moving process of the platform, a certain distance is taken as an interval, each step of moving is carried out, noise signals radiated by a target are received once, and acoustic propagation time difference (arrival time difference) between array elements at the current platform position is calculated according to the received noise signals, and the time difference is called inter-array element time difference for short; when the platform moves to the current position (the kth step), the target function is solved by utilizing the platform positions of a plurality of previous steps (such as N steps) and the measured time difference information between array elements; searching and positioning the target by using an optimization method for searching the minimum value of the target function to obtain a positioning estimation result of the current position (current step) of the platform; then, taking the platform position as a variable, calculating a new target function and a negative gradient direction of the target function to the platform position, taking the projection of the negative gradient direction on a horizontal plane as the next platform moving direction for the platform moving only in the horizontal direction, and enabling the platform to move a certain distance (one step) to reach the next position towards the projection direction; obtaining a new time difference of arrival at the location and updating the positioning estimate; the above process is repeated until a preset objective function value (set according to the positioning accuracy) is reached, or a preset number of positioning steps is reached.
The target positioning method of the invention comprises the following steps: based on the objective function provided by the invention, the target is positioned by an optimization process of searching the minimum value of the objective function at each step in the moving process of the platform, and specific optimization methods can be various, such as a gradient descent algorithm, a simulated annealing algorithm, a genetic algorithm, a particle swarm algorithm, a foraging algorithm and the like. The present invention uses a gradient descent method (also called steepest descent method) of an objective function as an example, but not limited to the gradient descent method, to describe the process of target positioning. The method for realizing the rapid convergence of the target positioning through the platform track optimization provided by the invention comprises the following steps: each step of the platform is enabled to move for a certain distance along the negative gradient direction of the target function for the platform position, but the platform is not limited to the track, and the target is rapidly positioned in the platform moving process; the method is an optimization method with a fast convergence speed for solving the problem, and ensures that the platform shifts towards the direction which enables the target function to descend fastest every time the platform moves, and the moving distance (step length) of each step can be determined according to the practical application environment, or different step lengths can be adopted for each step.
The invention is illustrated on the basis of the model of fig. 1. In the coordinate system shown in fig. 1, xy is the horizontal direction, and z is the height direction; o is1…OnThe method comprises the steps of representing the platform center position of target positioning in each time (each step) in the platform moving process, defining the direction from the platform center to the current target estimated position as a radial direction, and defining the direction perpendicular to the radial direction as a tangential direction.
1. The invention discloses a high-precision passive sound positioning method of a mobile platform, which comprises the following specific steps:
1.1 setting initial position of the platform and initial positioning value of the target to be detected:
setting an initial position of a platform:
setting an initial positioning value of a target to be detected:
1.2 time difference measurement at the current platform position (step k, k is more than or equal to 1).
1.2.1 multichannel acoustic signal acquisition of the current position.
Multichannel acoustic signal acquisition is realized through multichannel preamplification, filtering and analog-to-digital conversion (A/D), and acoustic signals of acoustic waves radiated by a target sound source at the current position of the platform and transmitted to all receiving array element (hydrophone) channels through a water medium are obtained.
1.2.2 time difference calculation of current position.
And (3) defining a reference array element, and calculating the time difference (time difference for short) between the target and each array element and the reference array element by using a high-precision time difference measurement algorithm based on the acoustic signals acquired by the multiple channels in the step (1.2.2). In actual operation, any one array element can be manually specified as a reference array element, and the time difference between the target and each array element and the reference array element is calculated. For simplicity of representation, a reference array element may be defined as i-1, and the other array elements are renumbered as i-2, 3, …, m. The time difference between the underwater target to the (i + 1) th array element and the reference array element (array element 1) is:
Δti＝ti+1-t1 (i＝1,2,…,m-1) (1)
by utilizing the correlation of the acoustic signals of any two array element channels, high-precision time difference measurement methods such as a cross-correlation method, a cross-power spectrum method and the like can be applied to realize the time difference delta tiAccurate measurement of.
1.3 calculating the objective function at the current platform position (the kth step, k is more than or equal to 1).
1.3.1 updating the current array element position information.
Based on the current (kth) known position of the mobile platform, the labels are:
the positions of the array elements obtained by calculating the current platform position are respectively as follows:
wherein the current position of the ith array element is
The position of each array element relative to the coordinate origin of the platform can be calculated according to the position of each array element in the coordinate system of the platform and the attitude of the platform.
1.3.2 calculate the current range difference vector.
Setting the position to be estimated of the current (k step) target as:
defining the distance difference between each array element and the reference array element (array element 1) to the current target position to be estimated as delta Ri，(i＝1,2,…,m-1)：
ΔRi＝Ri+1-R1 (3)
Wherein R isiThe distance from the current target to the ith array element is estimated, which can be calculated according to the geometrical relationship as follows:
defining the time difference of arrival Deltat between each array element and a reference array element (array element 1)iThe observed distance difference is array element observed distance difference delta R'i，(i＝1,2,…,m-1)：
ΔR'i＝cΔti (5)
Where c is the speed of sound in water.
Defining differences between estimated range differences between array elements and observed range differences between array elements as range difference vectors
Wherein
gi＝ΔRi-ΔR'i (i＝1，2，…，m-1) (7)
1.3.3 finds the objective function at the current location.
Based on the current target position to be estimated:
calculating distance difference vector of all platform positions in previous N steps
And N is the step number set according to practical application. For a mobile platform, the invention proposes a new objective function definition as:
for the first few steps (less than N steps), i.e. k < N, the objective function can take:
1.4 target positioning algorithm based on minimum value search of target function.
The target positioning algorithm based on the target function minimum search can be any optimization algorithm based on a gradient descent method, a simulated annealing algorithm, a genetic algorithm, a particle swarm algorithm, a foraging algorithm and the like. Taking the gradient descent method as an example but not limited to the gradient descent method in the following (1.4.1) - (1.4.5), a target location algorithm based on the target function minimum search algorithm is briefly described.
1.4.1 setting the initial value of the target position estimation and the convergence condition in the k step.
The initial value of the target position estimation is as follows:
the preset convergence conditions are as follows: the value of the objective function is JkminAnd iteration step number Nkmax。
1.4.2 calculating the objective function at the j iteration at the current position (step k)
According to each of the steps (1.3), using the previous N steps (or k steps, if k is<N) platform position and the arrival time difference information of the step (1.2), and calculating the objective function of the j iteration at the current position (the k step) as
1.4.3 calculating the (1.4.2) th objective function versus target position coordinates
Gradient (2):
1.4.4 update the estimate of the target position.
Target position of current iteration number j
Adding the product of the negative gradient and the step coefficient to obtain a new estimated target position
Wherein mu is a step coefficient and can be adjusted according to actual conditions.
1.4.5 iteration end decision.
Judging the value of the current objective function, if it is less than or equal to (1.4.1) the preset convergence objective function value JkminThen the iteration is terminated; if the preset objective function value is not reached, but the preset step number Nk of (1.4.1) is reachedmaxTerminating the iteration; otherwise, repeating the steps (1.4.2) - (1.4.5) until the termination condition is reached.This result is used as the final target location estimate for the platform movement to the current position (kth step):
and (4) calculating the target function set value of the convergence condition in the step (1.4.1) according to the positioning error or the positioning precision requirement. A very small value is typical under high signal-to-noise ratio conditions; under the condition of low signal-to-noise ratio, the estimated distance measurement error can be set according to the difference of time difference measurement errors caused by the signal-to-noise ratio.
2. The invention relates to a method for realizing rapid positioning of a target through track optimization, which comprises the following specific steps:
2.1 predetermined Convergence objective function value JminAnd the maximum number of steps N of the platformmax.
2.2 calculate the objective function at the current stage position (step k).
2.2.1 compute the distance difference vector at the current stage position (step k).
And (4) according to the target positioning estimation finally obtained in the step (1.4):
re-calculating the distance difference vector at the current platform position according to the steps (1.1) to (1.3):
2.2.2 calculate the objective function at the platform location (step k):
2.3 calculate the gradient of the current position (step k) objective function to the platform position coordinates:
2.4 updating the position of the platform.
The next position of the platform is the current position plus the product of the negative gradient direction and the step length d, i.e.:
wherein d is the step length (distance) of the platform moving offset; the specific operation can be performed by taking a fixed step length, and a variable step length can also be adopted according to an actual application scene.
Typically, the platform is typically at a fixed depth z0Is moved in the horizontal direction, i.e.
Therefore, in the calculation (13), only the two-dimensional projection of the gradient on the (x, y) plane needs to be calculated, and in the calculation (14), only the two-dimensional projection direction of the gradient on the (x, y) plane needs to be adopted to update the two-dimensional coordinates (x, y) of the platform.
2.5 judging whether the convergence condition reaches the set value.
Judging the objective function value at the current platform position (k step), if the objective function value is less than or equal to (2.1) the preset convergence objective function value JminThen the iteration is terminated; if the preset objective function value is not reached, but the preset step number N is reached (2.1)maxTerminating the iteration; otherwise, repeating the steps (2.2) - (2.5) until the termination condition is reached. Taking the result as a final target positioning estimation of the platform:
the preset convergence condition of the step (2.1) may be a preset mean square error; or a mean square error value calculated according to a preset standard deviation or a preset deviation.
The convergence condition setting value is calculated according to the positioning error or the requirement of the positioning precision. A very small value is typical under high signal-to-noise ratio conditions; under the condition of low signal-to-noise ratio, the estimated distance measurement error can be set according to the difference of time difference measurement errors caused by the signal-to-noise ratio.
The invention brings the technical effects that:
the mean square error of continuous and repeated positioning results in the platform moving process is used as a target function for carrying out optimal estimation on the target position and planning the platform moving path, so that the positioning error can be converged to a preset error quickly, and high-precision passive acoustic positioning is realized. In addition, due to the path planning using the gradient descent method, the number of positioning times required to meet the positioning accuracy requirement is the smallest of all paths.
Drawings
FIG. 1 is a basic principle of passive acoustic localization of an object in water by a mobile platform;
fig. 2 is a schematic diagram of the array structure of the 4-element array and the 9-element array.
Fig. 2(a) shows a 4-element array, and fig. 2(b) shows a 9-element array.
FIG. 3 is a graph comparing the root mean square error convergence curves of the planned path and the fixed path.
Fig. 3(a) is the result obtained by the 4-element array shown in fig. 2, and fig. 3(b) is the result obtained by the 9-element array shown in fig. 2.
Fig. 4 is a comparison graph of the convergence curves of the planned paths with different array element numbers.
Detailed Description
In order to make the aforementioned features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
The mobile platform adopts two cubic array types of 4-element array and 9-element array, as shown in fig. 2(a) and (b).
The target position is a random point 1000m away from the center of the platform, the target is set to be a linear frequency modulation signal of 1kHz-10kHz, the signal to noise ratio is set to be 20dB, noise is marine environment noise, and the time difference measurement is carried out by applying an improved cross-correlation method. And positioning the target by using a gradient descent method, and continuously correcting the current positioning center until the target is converged to the required positioning precision. The convergence condition set in this example is a distance relative error of 0.2%.
The simulation times are 1000 times, and the positioning mean value and the root mean square error of each step are obtained. And taking the mean absolute value of the root mean square errors of all 1000 positioning results of each step as an index of positioning accuracy. In order to embody the characteristic that the planned path can rapidly improve the precision, the positioning result of the platform moving along the planned path for the first 10 times is selected to be compared with the result of the platform moving along the radial direction or the tangential direction. The three paths have the same root mean square error value at the beginning. For planning the path, an optimal fixed step factor γ is first determined, and for better comparison with the results of radial and tangential movement, we set the fixed step factor to be less than 20, thus ensuring that the total path length D is not too long. And the result that the root mean square error is reduced to 2m most quickly and the corresponding planned path are obtained by taking the relative positioning accuracy of 0.2 percent as a convergence target. Under the condition, the root mean square error convergence curves brought by the planned path and the two fixed paths are shown in figure 3. it can be seen that the required positioning precision (2m) can be converged by adopting the positioning method of the invention in any path, and the convergence speed is higher by adopting the planned path.
Under the same simulation conditions, the planning track root-mean-square error convergence curves of the two array element numbers are compared, the conditions of the 4-element array and the 9-element array are simulated respectively, and the result is shown in the attached figure 4.
From the simulation results we can conclude that: the planned path generally deviates to the tangential direction for a certain distance and then gradually trends to the radial direction, which shows that when the planned path is far away from the target, the tangential movement of the platform can bring about the rapid improvement of the positioning precision, and the radial approach can improve the upper limit of the positioning precision along with the increase of the positioning times; the planning path has a faster convergence speed for improving the positioning result than the fixed path and approaches the positioning accuracy required to be met; for two simulation results with different array element numbers, the relative accuracy of the positioning distance of the final positioning result of 10 times can reach below 0.2 percent, and the relative accuracy of 9 array elements reaches 0.1 percent; the method shows that more array elements have higher positioning accuracy and faster convergence speed; and finally, as the platform is closer to the target, the positioning times are increased, and as long as the number of the array elements is more than 4, the root mean square error curve gradually approaches 0 no matter the number of the array elements.
The above embodiments are only intended to illustrate the technical solution of the present invention and not to limit the same, and a person skilled in the art can modify the technical solution of the present invention or substitute the same without departing from the spirit and scope of the present invention, and the scope of the present invention should be determined by the claims.
Claims (8)
1. A passive acoustic positioning method of a moving platform on an underwater target comprises the following steps:
1) the method comprises the steps that a mobile platform receives a noise signal radiated by an underwater target once in each moving step; wherein, one step is a set distance length;
2) calculating the sound propagation time difference between the array elements on the mobile platform at the current position according to the noise signals;
3) calculating a target function of the current position of the mobile platform by utilizing a plurality of previously calculated sound propagation time differences and the corresponding positions of the mobile platform;
4) searching and positioning the underwater target by using an optimization method for searching the minimum value of the target function to obtain a positioning estimation result of the current position of the mobile platform on the underwater target;
the method for solving the objective function of the current position of the mobile platform comprises the following steps:
31) the current position of the mobile platform after the k step is set as
The current position of the ith array element on the mobile platform
The position of the ith array element relative to the origin of the mobile platform; i-1, 2, …, m, whichM is the total number of array elements on the mobile platform;
32) setting an array element as a reference array element, and setting the estimated position of the current underwater target as
The distance difference delta R between the ith array element and the current underwater target estimation position from the reference array elementi＝Ri+1-R1,i＝1,2,…,m-1；RiEstimating the distance from the position to the ith array element for the current underwater target; r1Estimating the distance from the position to a reference array element for the current underwater target;
33) according to the acoustic propagation time difference delta t from the current position of the underwater target to the ith array element and the reference array elementiCalculating inter-array element observation distance difference delta R'i＝cΔtiThen calculating a distance difference vector
Wherein, gi＝ΔRi-ΔR′iI is 1,2, …, m-1, c is the speed of sound in water;
34) generating an objective function
Wherein k is the current moving step number of the mobile platform, and N is the set step number; if k is<N, then the objective function is
2. The method as claimed in claim 1, wherein in the step 4), the method for searching and locating the underwater target by using the optimization method for finding the minimum value of the objective function comprises:
41) setting the estimated initial value of the target position in the k step as
Setting the convergence condition of the k step;
42) calculating the objective function of j iteration at the current k step by using the position of the mobile platform and the corresponding sound propagation time difference information in a plurality of previous steps
And estimating location coordinates for the target
Gradient of (2)
43) Target position of current iteration number j
Adding the product of the negative gradient and the step coefficient to obtain a new estimated target position
Mu is a step size coefficient;
44) if the convergence condition is reached, terminating the iteration; otherwise, repeating the steps 42) to 43) until reaching the termination condition, and obtaining the final target positioning estimation at the k-th step of the mobile platform movement
3. The method as claimed in claim 2, wherein the convergence condition of the k-th step is an objective function value JkminIteration step number Nkmax(ii) a The method for judging whether the convergence condition is reached comprises the following steps: if the value of the current objective function is less than or equal to the value of the objective function JkminThen the iteration is terminated; if the target function value Jk is not reachedminBut reaches a predetermined number of steps NkmaxThe iteration is terminated.
4. The method of claim 1, wherein the positioning estimation result obtained in step 4) is optimized by:
51) set termination condition convergence objective function value JminAnd the maximum moving step number N of the mobile platformmax；
52) According to the target positioning estimation result obtained in the k step
Recalculating the range difference vector at the kth step position of the mobile platform
53) Calculating an objective function at the kth step of the mobile platform
And its gradient to the current position coordinates of the mobile platform
54) Updating the position of the mobile platform to
Wherein d is the step length of the mobile offset of the mobile platform;
55) if the objective function value at the k step of the mobile platform is less than or equal to the convergence objective function value JminThen the iteration is terminated; if the convergence objective function value J is not reachedminBut up to step number NmaxThen the iteration is terminated; otherwise, repeating the steps 52) to 54) until reaching the termination condition to obtain the final target positioning estimation result
5. The method of claim 4, wherein the mobile platform is set at a fixed depth z0Is moved in the horizontal direction, i.e.
Calculating gradients
And (3) two-dimensional projection on an (x, y) plane, and updating the two-dimensional coordinate (x, y) position of the mobile platform by adopting the two-dimensional projection direction of the gradient on the (x, y) plane.
6. The method of claim 1, wherein the optimization method is a simulated annealing algorithm, a genetic algorithm, a particle swarm algorithm, or a foraging algorithm.
7. The method of claim 1, wherein the moving direction of the moving stage at step k +1 is a direction along the negative gradient of the objective function at step k with respect to the position of the moving stage at step k.
8. The method of claim 1, wherein the array elements are hydrophones.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910405417.9A CN110196425B (en) | 2019-05-16 | 2019-05-16 | Passive acoustic positioning method for underwater target by mobile platform |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910405417.9A CN110196425B (en) | 2019-05-16 | 2019-05-16 | Passive acoustic positioning method for underwater target by mobile platform |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110196425A CN110196425A (en) | 2019-09-03 |
| CN110196425B true CN110196425B (en) | 2021-03-12 |
Family
ID=67752977
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910405417.9A Active CN110196425B (en) | 2019-05-16 | 2019-05-16 | Passive acoustic positioning method for underwater target by mobile platform |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110196425B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112083402B (en) * | 2020-09-15 | 2022-12-13 | 哈尔滨工程大学 | Underwater target sailing detection experimental method under pool condition |
| CN112817332B (en) * | 2021-01-06 | 2022-03-25 | 浙江大学 | Underwater vehicle hidden path planning method based on marine environment |
| CN114578287B (en) * | 2022-02-28 | 2024-05-24 | 哈尔滨工程大学 | Fusion positioning method based on multi-base buoy array improved simulated annealing |
| CN115508837B (en) * | 2022-09-13 | 2024-04-30 | 西北工业大学 | Mobile multi-base sonar target positioning and error analysis method based on UUV cluster |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101470196A (en) * | 2007-12-26 | 2009-07-01 | 中国科学院声学研究所 | System and method for passively positioning underwater target |
| EP2435806B1 (en) * | 2009-05-27 | 2016-07-06 | Teledyne Instruments, Inc. | Method and system for remote sound speed measurement |
| CN107479031A (en) * | 2017-07-24 | 2017-12-15 | 哈尔滨工程大学 | A kind of hidden underwater Passive Location |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102890265B (en) * | 2012-08-09 | 2014-05-14 | 西北工业大学 | Passive target positioning method based on underwater acoustic sensor network |
| CN103176166B (en) * | 2013-03-14 | 2015-03-04 | 东南大学 | Tracking algorithm for time difference of arrival of signals for acoustic passive positioning |
| RU2556302C1 (en) * | 2014-03-11 | 2015-07-10 | Федеральное государственное бюджетное учреждение науки Тихоокеанский океанологический институт им. В.И. Ильичева Дальневосточного отделения Российской академии наук (ТОИ ДВО РАН) | Method for passive acoustic location of underwater divers |
| CN106054135B (en) * | 2016-05-12 | 2018-08-21 | 东南大学 | A kind of passive underwater acoustic localization method based on period traveling time window |
| JP6724593B2 (en) * | 2016-06-22 | 2020-07-15 | 日本電気株式会社 | Active sonar and control method of active sonar |
| JP6402224B1 (en) * | 2017-07-26 | 2018-10-10 | 株式会社ＡｑｕａＦｕｓｉｏｎ | Acoustic sounding device and acoustic sounding method |
| CN108318863B (en) * | 2017-12-28 | 2020-11-24 | 浙江大学 | Submarine beacon-based passive positioning method and system for underwater unmanned equipment |
-
2019
- 2019-05-16 CN CN201910405417.9A patent/CN110196425B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101470196A (en) * | 2007-12-26 | 2009-07-01 | 中国科学院声学研究所 | System and method for passively positioning underwater target |
| EP2435806B1 (en) * | 2009-05-27 | 2016-07-06 | Teledyne Instruments, Inc. | Method and system for remote sound speed measurement |
| CN107479031A (en) * | 2017-07-24 | 2017-12-15 | 哈尔滨工程大学 | A kind of hidden underwater Passive Location |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110196425A (en) | 2019-09-03 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110196425B (en) | Passive acoustic positioning method for underwater target by mobile platform | |
| CN108427414B (en) | Horizontal plane self-adaptive trajectory tracking control method for autonomous underwater vehicle | |
| CN108614258B (en) | Underwater positioning method based on single underwater sound beacon distance measurement | |
| CN111273298B (en) | Underwater acoustic target positioning and tracking method based on wave glider networking technology | |
| CN108267731B (en) | Construction method and application of unmanned aerial vehicle target tracking system | |
| KR102218582B1 (en) | System for underwater localization | |
| CN111928850A (en) | Combined navigation method of autonomous underwater robot suitable for environment under polar ice frame | |
| Masmitja et al. | Range-only single-beacon tracking of underwater targets from an autonomous vehicle: From theory to practice | |
| CN111551942B (en) | Underwater autonomous vehicle docking method based on deconvolution algorithm | |
| CN110132281A (en) | A kind of autonomous acoustic navigation method of underwater high-speed target with high precision based on inquiry answer-mode | |
| CN111735455A (en) | Improved Gaussian distance iterative algorithm based butt joint recovery integrated navigation method | |
| CN105738869A (en) | Deepwater beacon searching and positioning method suitable for single hydrophone | |
| CN116125386A (en) | Intelligent positioning method and system for underwater vehicle with enhanced sparse underwater acoustic ranging | |
| CN112666519B (en) | High-precision underwater target positioning method based on generalized second-order time delay difference | |
| KR102329472B1 (en) | Apparatus and method for compensating distance calculation error of Passive Ranging Sonar | |
| CN109975760B (en) | High-precision calibration method and device for array installation error angle based on double-vector reconstruction | |
| CN112684411B (en) | Underwater target positioning method based on improved arrival frequency difference | |
| CN110989655A (en) | Target tracking method for ship-based reconnaissance and shooting unmanned aerial vehicle in take-off and landing stages | |
| Maki et al. | AUV HATTORI: A lightweight platform for high-speed low-altitude survey of rough terrains | |
| CN109239666A (en) | A kind of calibration method for deep-sea acoustic positioning device | |
| CN110068798B (en) | Quaternary receiving sparse array form and signal receiving method of underwater autonomous vehicle | |
| Hamamatsu et al. | Short range tracking method of underwater vehicles based on vision | |
| CN110703187B (en) | Acoustic beacon direction finding and positioning method based on underwater mobile platform | |
| Liu et al. | Autonomous underwater glider navigation with single seabed beacon | |
| Matsuda et al. | State estimation of multiple autonomous underwater vehicles for wide area survey of seafloor |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |