Underwater multi-station speed measurement technology based on acoustic beacon

Abstract

The invention belongs to the field of underwater target navigation and positioning, and discloses an underwater multi-station speed measurement technology based on acoustic beacons, which comprises the following specific steps: 1) establishing a coordinate system, acquiring measurement information, and estimating the initial position of a navigation body; 2) sound velocity correction and position parameter estimation are carried out point by point, and speed parameter estimation is carried out after iterative calculation of position parameter convergence; and 3) estimating a constraint polynomial coefficient, and optimizing the position and speed parameters of the navigation body. The technology has the characteristics that the observation process does not depend on a navigation body, the measurement precision is high, the result can be accurately obtained in real time and the like, reliable estimation of position and speed parameters based on polynomial constraint under a complex navigation working condition is realized, and the problems of functional expression of observation motion under a high-dynamic motion condition and provision of continuous and smooth motion parameters are solved; the method has good adaptability to the complex motion process of an underwater target, has a wide technical application prospect, and can provide a data processing and analysis technology for underwater motion performance analysis and evaluation of a navigation body.

Description

Technical Field

[0001] The present invention belongs to the field of underwater target navigation and positioning, and specifically relates to an underwater multi-station speed measurement technology based on acoustic beacons. The present invention is a technology that utilizes acoustic beacons and multi-station mounted receiving equipment to achieve underwater motion speed measurement without relying on the conditions of the navigation body itself. Background Art

[0002] Affected by factors such as R&D costs, operating conditions, and marine environment, it is difficult to obtain motion data during underwater testing of navigation bodies. At present, the main method used is to install inertial sensors inside the navigation body to obtain parameters such as acceleration and angular velocity, and then obtain information such as speed, position, and attitude through data processing. This method of obtaining data is relatively mature and reliable, but it also has inherent defects. The drift error of inertial devices accumulates over time, and the positioning error is large during long-term navigation. Another internal measurement method is to install a Doppler odometer on the navigation body, and use the Doppler frequency shift between the transmitted sound waves and the received seabed reflected sound waves to measure the speed and cumulative distance of the ship relative to the bottom of the water. Its technology is also relatively mature. Both of the above methods rely on the navigation body itself. The data is recorded and processed on the navigation body, which is suitable for post-analysis. When the navigation body cannot be recovered normally due to a malfunction, it is difficult to obtain its underwater motion process and status information.

[0003] In contrast, hydroacoustic positioning technology is an external observation technology that does not rely on navigation. Currently, a variety of positioning modes such as ultra-short baseline, short baseline, and long baseline have been developed. With the installation of acoustic beacons, robust positioning performance and high positioning accuracy can be achieved. However, hydroacoustic positioning technology is closely related to the actual working conditions and environmental conditions. Any hydroacoustic positioning system has its scope of application and conditions. For local underwater navigation with strong maneuverability and high dynamics, in order to accurately measure and identify its motion characteristics, targeted technical designs need to be adopted in combination with specific working conditions. In particular, for the measurement of velocity parameters, if the conventional position difference method is used for calculation, the obtained sequence values ​​will show large random fluctuations, which is difficult to meet the requirements of the motion performance analysis of the navigation body.

[0004] In recent years, with the advancement of underwater acoustic technology, the performance of acoustic beacons has been continuously improved. Technologies such as high-frame rate positioning acoustic signal provision, robust estimation of radial velocity, and high-precision underwater station calibration have been developed, providing a technical basis for solving the problem of high-precision underwater speed measurement of navigation bodies under external measurement conditions. In order to solve the problem of high-reliability speed measurement for underwater performance evaluation of navigation bodies, it is urgent to develop underwater motion parameter external measurement technology based on acoustic beacons. Summary of the invention

[0005] To solve the above problems, the present invention proposes a technology for underwater motion speed measurement that is independent of the navigation body itself by using acoustic beacons and multiple measuring station-mounted receiving devices. The acoustic positioning system based on acoustic beacons provides slant range and radial velocity information, and the position and velocity are solved in combination with the measuring station position, and then the polynomial constraint method is used to achieve the optimization estimation of the entire sequence. This technology has the characteristics of independent observation process from the navigation body, high measurement accuracy, quasi-real-time acquisition of results, and smooth and continuous data. It can adapt to local complex underwater navigation processes with strong maneuverability and high dynamics, and has practical value for the analysis and evaluation of underwater motion performance of navigation bodies.

[0006] The technical solution of the present invention is:

[0007] An underwater multi-station speed measurement technology based on acoustic beacons, firstly, establishes a unified coordinate system, aligns the station position, sound speed profile and other information, obtains the arrival delay and radial velocity estimation value, and estimates the initial position of the vehicle; secondly, through the iterative operation of sound speed correction and position parameter estimation, the point-by-point solution results of the vehicle position and velocity parameters are obtained; finally, a reasonable polynomial constraint function is selected, and the function coefficients are identified using the point-by-point solution results of the position and velocity parameters, and the optimized position and velocity parameter sequence of the vehicle is obtained based on the polynomial expression.

[0008] The specific steps are as follows:

[0009] Step 1: Establish initial measurement information

[0010] (1.1) Establishing the coordinate system

[0011] Establish the station coordinate system, select a theoretical position point in the measurement area, set its elevation zero point as the origin O, the OX axis points to the east, the OY axis points to the north, and the OZ axis points vertically upward. Suppose the target position of the navigation body to be measured is X = [x, y, z], and the speed is Both the measurement information and parameter estimation results are matched to this coordinate framework.

[0012] (1.2) Obtaining measurement information

[0013] Under the condition of multiple stations deployed at sea, the location information of each station is obtained through satellite navigation positioning, inertial sensors, hydroacoustic positioning and other technical means. The coordinates of station j are N is the number of measuring stations (N≥3).

[0014] The sound velocity profile c(z) is obtained through field measurements, and the specific information includes the sound velocity values ​​that vary with depth and the observation location.

[0015] Under the condition of acoustic beacon, the receivers carried by each measuring station are used to detect, process and record the arrival acoustic signals. The arrival delay and radial velocity estimation are completed by using the prior information of the positioning acoustic signal design and combining the sound speed information measured on site, and the delay vector is obtained. and the radial velocity vector

[0016] (1.3) Initial position estimation

[0017] From N measuring stations, select 3 of them and set their numbers to 1 # -3 # , of which 3 # The measuring station is a reference station and makes a preliminary estimate of the target position.

[0018] The slope distance between the target and the measuring station is:

[0019]

[0020] 1 # , 2 # Station and 3 # The baseline length of the station is:

[0021]

[0022] The initial position estimate X is obtained as follows: 0 =[x 0 ,y 0 ,z 0 ] T :

[0023]

[0024] in:

[0025]

[0026] cosθ=λ1λ2+μ1μ2+ν1ν2, sinθ=(1-cos 2 θ) 1 / 2

[0027] Step 2: Solve the position and speed parameters point by point

[0028] (2.1) Sound speed correction and position parameter estimation

[0029] According to the delay vector The estimated slant distance between the target and the measuring station can be calculated by combining the sound velocity profile c(z) as follows:

[0030]

[0031] in:

[0032]

[0033] Then the target position is estimated as follows:

[0034]

[0035] in:

[0036]

[0037] (2.2) Iterative calculation of position parameters

[0038] Get the estimated target position After that, ||ΔX||2 is used as the criterion to determine whether the predetermined convergence accuracy has been reached; if not, the position estimate is updated to the initial position value X of the next iteration. 0 , iteratively calculate according to the method described in (2.1) until it converges to the required accuracy.

[0039] (2.3) Speed ​​parameter estimation

[0040] Get the target position estimate that meets the convergence accuracy After that, the estimated value of the speed parameter is obtained as follows:

[0041]

[0042] Step 3: Estimate constraint polynomial coefficients and optimize position and velocity parameters

[0043] (3.1) Polynomial coefficient estimation

[0044] In a navigation sequence, the method of step 2 is used to solve point by point to obtain the estimated values ​​of the parameter sequence of position and speed. and (Wherein, the sequence number of the time series k = 1, 2, ..., K).

[0045] Taking into account the inevitable random errors in point-by-point observation data, which causes random "jitter" in the data, the position and velocity sequences are expressed as functions constrained by polynomials as follows:

[0046]

[0047] Where m (m≥2), p (p≥2), and q (q≥2) are the polynomial orders.

[0048] The polynomial coefficients are estimated using the estimated values ​​of the position and velocity parameter sequences obtained by point-by-point calculation:

[0049]

[0050] in:

[0051]

[0052] Thus, we get the polynomial coefficients C in the three directions of X, Y, and Z X =[a0,a1,…,a m ]、C Y =[b0,b1,…,b p ]、C Z =[c0,c1,…,c q ].

[0053] (3.2) Position and speed parameter optimization

[0054] Using the position and velocity polynomial constraints described in (3.1), y(t), z(t), Substitute the polynomial coefficients C X , C Y and C Z , get the optimized position and speed parameter sequence and (Wherein, the sequence number of the time series k = 1, 2, ..., K).

[0055] The beneficial effects of the present invention are as follows: the method is a technology for measuring underwater motion speed by using acoustic beacons and receiving devices carried by multiple measuring stations without relying on the conditions of the navigation body itself, fully considering the influence of the underwater acoustic channel on the measurement and the resulting fluctuations in the sequence data, and realizing reliable estimation of position and velocity parameters based on polynomial constraints under complex navigation conditions, solving the problems of functional expression of observed motion and provision of continuous and smooth motion parameters under high dynamic motion conditions, having good adaptability to the complex motion process of underwater targets, and having broad prospects for technical application, and can provide data processing and analysis technology for analysis and evaluation of underwater motion performance of navigation bodies. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is the basic process of the method proposed in the present invention.

[0057] Figure 2 It is the distribution map of target trajectory and measuring station location.

[0058] Figure 3 It is the slant distance sequence curve of the four stations in the regular quadrilateral array, where the horizontal axis is the time series and the vertical axis is the slant distance value.

[0059] Figure 4 It is the radial velocity series curve of the four measuring stations of the regular quadrilateral array, where the horizontal axis is the time series and the vertical axis is the radial velocity value.

[0060] Figure 5 The three-dimensional trajectory of the navigation body is given, and the point-by-point solution results, parameter estimation results and reference values ​​are compared in the figure.

[0061] Figure 6(a) and Figure 6(b) are the position and velocity sequence curves of the navigation body, respectively. The horizontal axis is the time series, and the vertical axis is the position value and the velocity value, respectively. The figure compares the point-by-point motion results, parameter estimation results and reference values. DETAILED DESCRIPTION

[0062] The specific implementation of the method proposed in the present invention is further described below in conjunction with the accompanying drawings and technical solutions.

[0063] The main steps of the present invention are as follows Figure 1 As shown. The following is an example of a group of underwater vehicles doing vertical motion, the goal is to obtain the velocity value of the vehicle at a characteristic moment. By processing and calculating according to the above steps, the rationality and effectiveness of the proposed method are explained.

[0064] (1) A regular quadrilateral measurement formation is selected, with four measuring stations located on the seafloor at the vertices of the quadrilateral. A group of vertical moving targets are measured. The motion trajectory of the vehicle and the distribution of the measuring stations are shown in Figure 2 After the vehicle starts to move, it will synchronously emit a positioning sound signal. Each station will receive the sound signal and obtain the delay vector after signal processing. and the radial velocity vector During this period, the sound velocity profile was measured synchronously. In the measurement coordinate system, the above measurement information was uniformly processed, and the target initial value X was obtained according to the method described in (1.3). 0 =[x 0 ,y 0 ,z 0 ] T .

[0065] (2) Based on the above measurement information, the sound velocity correction and position parameter iterative solution are completed according to the methods described in (2.1) and (2.2). The slant range sequence after the iteration is shown in Figure 3 Based on this set of slant distances, the target position estimation sequence is calculated point by point According to Figure 4 The radial velocity data shown is calculated according to the method described in (2.3), and the target velocity estimation value sequence is obtained point by point

[0066] (3) According to the motion characteristics of the navigation body, a third-order polynomial is constructed in the three directions of X, Y, and Z, that is, m = 3, p = 3, q ​​= 3. Using the estimated values ​​of the target position and velocity sequence obtained by point-by-point calculation, the estimated values ​​of the constraint polynomial coefficients are obtained according to the method described in (3.1), see Table 1. Substitute the polynomial coefficients into the expression of motion parameters in (3.1), and finally obtain the optimized position and velocity parameter sequence and Figure 5 6 and 7 respectively give the three-dimensional trajectory and position and velocity sequence curves of the vehicle during its motion. The figure compares the point-by-point motion results, parameter estimation results and reference values. It can be seen from the figure that the technology proposed in the present invention can accurately describe the high-dynamic motion process, effectively eliminate the "jitter" of the point-by-point calculated data, and maintain the continuity and smoothness of the parameter sequence.

[0067] Table 1 Estimated values ​​of constrained polynomial coefficients

[0068]

Claims

1. An underwater multi-station speed measurement technology based on acoustic beacons, characterized in that: Here are the steps: Step 1: Establish initial measurement information (1.1) Establishing the coordinate system Establish the station coordinate system, select a theoretical position point in the measurement area, set its elevation zero point as the origin O, the OX axis points to the east, the OY axis points to the north, and the OZ axis is vertically upward; Assume that the target position of the vehicle to be tested is X = [x, y, z], and the speed is The measurement information and parameter estimation results are matched to this coordinate framework; (1.2) Obtaining measurement information Under the condition of multiple stations deployed at sea, the location information of each station is obtained through satellite navigation positioning, inertial sensors, and hydroacoustic positioning technology. The coordinates of station j are N is the number of measuring stations, N≥3; The sound velocity profile c(z) is obtained through field measurements, including the sound velocity values ​​that vary with depth and the observation location; Under the condition of acoustic beacon, the receivers carried by each measuring station are used to detect, process and record the arrival acoustic signals. The arrival delay and radial velocity estimation are completed by using the prior information of the positioning acoustic signal design and combining the sound speed information measured on site, and the delay vector is obtained. and the radial velocity vector (1.3) Initial position estimation From N measuring stations, select 3 of them and set their numbers to 1 # -3 # , of which 3 # The station is a reference station, which makes a preliminary estimate of the target location; The slope distance between the target and the measuring station is: 1 # , 2 # Station and 3 # The baseline length of the station is: The initial position estimate X is obtained as follows: 0 =[x 0 ,y 0 ,z 0 ] T : in: cosθ=λ1λ2+μ1μ2+ν1ν2,sinθ=(1-cos 2 i) 1 / 2 Step 2: Solve the position and speed parameters point by point (2.1) Sound speed correction and position parameter estimation According to the delay vector Combined with the sound velocity profile c(z), the estimated slant distance between the target and the measuring station is calculated as follows: in: Then the target position is estimated as follows: in: (2.2) Iterative calculation of position parameters Get the estimated target position After that, ||ΔX||2 is used as the criterion to determine whether the predetermined convergence accuracy has been reached; if not, the position estimate is updated to the initial position value X of the next iteration. 0 , iteratively calculate according to the method described in (2.1) until it converges to the required accuracy; (2.3) Speed ​​parameter estimation Get the target position estimate that meets the convergence accuracy After that, the estimated value of the speed parameter is obtained as follows: Step 3: Estimate constraint polynomial coefficients and optimize position and velocity parameters (3.1) Polynomial coefficient estimation In a navigation sequence, the method of step 2 is used to solve point by point to obtain the estimated values ​​of the parameter sequence of position and speed. and Wherein, the sequence number of the time series k = 1, 2, ..., K; Represent the position and velocity sequence as a function constrained by a polynomial: Where m, p, q are the polynomial orders, m≥2, p≥2, q≥2; The polynomial coefficients are estimated using the estimated values ​​of the position and velocity parameter sequences obtained by point-by-point calculation: in: Thus, we get the polynomial coefficients C in the three directions of X, Y, and Z X =[a0,a1,…,a m ]、C Y =[b0,b1,…,b p ]、C Z =[c0,c1,…,c q ]; (3.2) Position and speed parameter optimization Using the position and velocity polynomial constraints described in (3.1), y(t), z(t), Substitute the polynomial coefficients C X , C Y and C Z , get the optimized position and speed parameter sequence and Among them, the sequence number of the time series is k=1,2,…,K.

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