CN112684207B - ADCP (advanced digital control Performance) speed estimation and correction algorithm for deep submersible vehicle - Google Patents

ADCP (advanced digital control Performance) speed estimation and correction algorithm for deep submersible vehicle Download PDF

Info

Publication number
CN112684207B
CN112684207B CN202011491308.2A CN202011491308A CN112684207B CN 112684207 B CN112684207 B CN 112684207B CN 202011491308 A CN202011491308 A CN 202011491308A CN 112684207 B CN112684207 B CN 112684207B
Authority
CN
China
Prior art keywords
speed
adcp
depth
error
manned submersible
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
Application number
CN202011491308.2A
Other languages
Chinese (zh)
Other versions
CN112684207A (en
Inventor
刘锡祥
盛广润
刘贤俊
赵立业
黄永江
张玉鹏
赵苗苗
王子璇
蒲文浩
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Southeast University
Original Assignee
Southeast University
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Southeast University filed Critical Southeast University
Priority to CN202011491308.2A priority Critical patent/CN112684207B/en
Publication of CN112684207A publication Critical patent/CN112684207A/en
Application granted granted Critical
Publication of CN112684207B publication Critical patent/CN112684207B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Abstract

An ADCP speed estimation and correction algorithm for a deep submersible manned vehicle comprises the following steps: 1) on the sea surface, the manned submersible is provided at the initial moment by using SINS/GPS combined navigationSpeed v to groundb(ii) a 2) ADCP operating in convection mode, measuring the relative current velocity of the manned vehicle
Figure DDA0002840757860000011
Deducing the ground speed v of a manned submersible by repeated measurement of multiple ADCP scansbAnd velocity of water flow
Figure DDA0002840757860000012
3) Submerging to the offshore bottom, deducing the error of the ground speed of the manned submersible by using the ground speed of the manned submersible obtained by the ADCP bottom tracking function and the overlapped ADCP measurement, and providing a method for realizing error correction on the ground speed and the water flow speed of the manned submersible in each depth unit layer. The invention solves the problems that the ground speed and the ocean current speed of the manned submersible are difficult to estimate and the speed error is accumulated along with time in the submerging process, and can realize that the ground speed and the ocean current speed are acquired in the submerging/floating process of the deep submersible and the reliable and accurate speed information is obtained by completing the error correction.

Description

ADCP (advanced digital control Performance) speed estimation and correction algorithm for deep submersible vehicle
Technical Field
The invention belongs to the technical field of high-precision underwater navigation positioning, and relates to an ADCP (adaptive Doppler Current profiler) speed estimation and correction algorithm for a deep submersible vehicle, which is particularly suitable for measuring the information of the ground speed and the ocean current speed of the submersible vehicle in deep sea operation.
Background
The ocean contains a large amount of mineral resources, biological resources, chemical resources and the like, so deep sea exploration has important significance. In the deep sea field scientific research and investigation operation, the manned submersible can carry scientists and technicians to accurately reach the deep sea complex environment, and provides an important research foundation for deep sea investigation, so that the scientific research which attaches importance to the development of the manned submersible is also the consensus of the strong ocean at present.
The ground speed and the ocean current speed of the manned submersible are very important support information in scientific investigation, underwater submarine battle and the like in deep sea complex environments. From the perspective of ocean traffic, the ground speed monitoring of the manned submersible can not be carried out by high-precision navigation and positioning, and reference is provided for navigation control and the like; from the military perspective, observing the ocean current velocity of the water area where the submersible is located to prevent the variation requires flow velocity measurement, and provides help for national defense construction. On the water surface, speed information of the carrier can be provided through a Global Navigation Satellite System (GNSS) or a Strapdown Inertial Navigation System (SINS) and other systems; however, in the area far away from the sea bottom after diving, the signal can not penetrate the deep part of the sea, so that the GNSS can not measure the ground speed of the manned submersible, and the DVL can not measure accurate ocean current speed information, so that how to obtain an accurate and reliable carrier and the accurate ocean current speed information can still be a difficult problem faced by the manned submersible in the diving process.
Patent literature (publication No. CN 110274591A): a navigation and positioning method of a manned submersible underwater. The speed of the carrier relative to the water flow is measured based on an Acoustic Doppler Current Profiler (ADCP), the ground speed of the manned submersible is deduced, and then the ground speed output by SINS navigation calculation is fused with the ground speed to form SINS/ADCP combined navigation. The core of the method is based on ADCP measurement and speed estimation, a combined navigation algorithm of a middle-layer water area is designed, and the problem that autonomous navigation positioning is difficult to realize underwater is solved. But during the time the manned vehicle is submerged from the beginning to the offshore floor: the ground speed of the manned submersible at the initial moment is only calculated and output by means of SINS navigation, and high precision cannot be guaranteed; the estimation speed based on ADCP measurement has errors in proportion to the diving mileage, the method does not consider the problem of speed estimation error accumulation, the condition of navigation positioning misalignment occurs, and a method for obtaining accurate and reliable ocean current speed information to realize water area observation is also unavailable.
Disclosure of Invention
Aiming at the problems, the invention provides an ADCP speed estimation and correction algorithm of a deep submersible manned submersible. Aiming at the current situation that GPS and DVL can not directly measure the speed of a carrier to the ground and the speed of ocean current in the diving process of a deep sea area, the invention provides the speed to the ground at the initial moment of a manned submersible vehicle through GPS/SINS combined navigation, then the speed to the ground and the speed of the ocean current of the carrier are estimated by using an ADCP (underwater vehicle) of the deep submersible vehicle, and based on the problem that the speed estimation error is accumulated along with the diving depth, the invention provides an ADCP speed estimation and correction algorithm of the deep submersible vehicle, which is characterized by comprising the following specific steps of:
(1) on the sea surface, the ground speed v of the manned submersible at the initial moment is provided by using SINS/GPS combined navigationb；
The method for providing the ground speed of the manned submersible at the initial moment through the SINS/GPS integrated navigation in the step 1 comprises the following steps:
s1.1: an SINS navigation resolving algorithm is adopted, an inertial measurement unit outputs angular velocity and specific force information, and navigation information, namely attitude, velocity and position, is output through solving of an inertial navigation mechanical arrangement equation; the navigation resolving equation under the navigation coordinate system is as follows:
Figure GDA0003475932460000021
Figure GDA0003475932460000022
Figure GDA0003475932460000023
wherein, the selectionSelecting a local geographic coordinate system as a navigation coordinate system n which is a coordinate system of north east; a carrier coordinate system b is a front right lower coordinate system; the inertia and earth coordinate systems are respectively marked as i and e,
Figure GDA0003475932460000024
representing a posture matrix from a carrier coordinate system to a navigation coordinate system;
Figure GDA0003475932460000025
the angular rate of the carrier coordinate system relative to the navigation coordinate system is projected under the carrier coordinate system, the angular rate of the earth coordinate system relative to the inertial coordinate system is projected under the navigation coordinate system, and the angular rate of the navigation coordinate system relative to the earth coordinate system is projected under the navigation coordinate system; vnRepresenting a projection of the ground speed in a navigation coordinate system;
Figure GDA0003475932460000026
specific force information representing an accelerometer output; gnRepresenting the projection of the gravity acceleration under the n system; l, lambda and h respectively represent latitude, longitude and altitude; rn、ReRespectively representing the curvature radius of the earth meridian circle and the Mao-unitary circle;
s1.2: the GPS navigation is used for resolving, and the speed and the position of the carrier can be measured based on the distance between the measuring station and the satellite:
Figure GDA0003475932460000027
in the formula, Xj、Yj、ZjIs the satellite position, the carrier position Xu、Yu、ZuDetected in real time by the GPS; c is the propagation velocity of the electromagnetic wave;
Figure GDA0003475932460000028
the deviation of the signal receiver clock relative to the GPS time system;
Figure GDA0003475932460000029
is then the firstThe deviation of the clocks of the k GPS satellites relative to the GPS time system;
Figure GDA00034759324600000210
respectively, the distance deviations caused by the ionosphere and the troposphere;
according to the relationship between the speed and the distance change rate, a three-dimensional speed expression is obtained as follows:
Figure GDA00034759324600000211
the GPS receiver can measure the station satellite distance rhojAnd rate of change thereof
Figure GDA00034759324600000215
Figure GDA00034759324600000212
When the positioning calculation is carried out, the formula (5) only has four unknown numbers, and the speed of the carrier
Figure GDA00034759324600000213
And
Figure GDA00034759324600000214
all unknowns can be solved as long as 4 satellites are measured;
Figure GDA0003475932460000031
in the formula
Figure GDA0003475932460000032
Finally, the three-dimensional speed v of the carrier can be solved according to four equationsnAnd location information;
s1.3: on the sea surface, when the GPS works normally, the difference between the position and the speed of the SINS and the GPS is used as measurement information and sent into a Kalman filter to obtain a discretized Kalman filtering equation and a measurement equation, the SINS error is corrected, and more accurate and reliable navigation information is output;
s1.4: further, provided according to SINS/GPS
Figure GDA0003475932460000033
VnAnd position (L, lambda, h) and the like, and the ground speed V of the manned submersible at the initial moment is obtained by the following formulab；
Figure GDA0003475932460000034
(2) ADCP operating in convection mode, measuring the relative current velocity of the manned vehicle
Figure GDA0003475932460000035
Deducing the ground speed v of a manned submersible by repeated measurement of multiple ADCP scansbAnd velocity of water flow
Figure GDA0003475932460000036
In the step 2, the convection velocity of the manned submersible is measured through ADCP: ADCP firstly transmits sound wave signals with certain frequency to seawater, because scattering particles exist in the water, a part of scattering echo signals are received by a receiving transducer, because Doppler frequency shift exists between the transmitted sound wave and the scattering echo frequencies, the relative speed of the wave beam direction is obtained through frequency shift calculation, and then the wave beam direction is converted into the speed under a carrier coordinate system through the included angle of the wave beam direction
Figure GDA0003475932460000037
(3) Submerging to the offshore bottom, deducing the error of the ground speed of the manned submersible by using the ground speed of the manned submersible obtained by the ADCP bottom tracking function and the overlapped ADCP measurement, and providing a method for realizing error correction on the ground speed and the water flow speed of the manned submersible in each depth unit layer;
the step 3 is submerged to the offshore bottom, the error of the ground speed of the manned submersible is deduced by using the ground speed of the manned submersible obtained by the ADCP bottom tracking function and the overlapped ADCP measurement, and the method for realizing error correction of the ground speed and the water flow speed of the manned submersible in each depth unit layer is as follows:
s3.1: when the deep diving manned submersible reaches the near seabed, the bottom tracking method can be used to enable the seabed to reflect the signals to obtain echo signals, the Doppler frequency shift of the reflected signals is calculated, and the ground speed v of the manned submersible is obtainedb(track) thereby obtaining the ocean current velocity of the depth cell
Figure GDA0003475932460000038
S3.2: the ground speed v of the manned vehicle will be derived using the overlapped ADCP measurementsb(binN) And the ground speed v of the manned submersible acquired by using the ADCP bottom tracking methodb(trackN) Performing difference making to obtain the error delta v of the ground speed of estimation and measurementb(N); the ocean current velocity derived from the overlapped ADCP measurement is also differed from the ocean current velocity calculated under the bottom tracking method
Figure GDA0003475932460000039
S3.3: according to the characteristic that estimation errors of the manned submersible vehicle and the ocean current speed are in linear relation with the submergence time and the depth, the depth from the initial submergence time to the offshore bottom is assumed to be h meters, the depths of all units of ADCP are known to be d meters, the total number of depth units is N-h/d, the units are sequentially sequenced, the earth and ocean current speeds of each layer of depth unit are known according to the step 2, and the error of the earth speed of the manned submersible vehicle in each layer of depth unit is delta vb(n)＝(δνb(N)/N)·binn(ii) a An ocean current velocity error of
Figure GDA0003475932460000041
Since the ground speed of the first layer depth unit can be controlled by the navigation systemSystematic solution, no overlapped ADCP measurement estimation is needed, so n is more than 1;
s3.4: by the error estimation method, the speed error of each layer of depth unit is taken as a reference, and the speed deduced by the overlapped ADCP measurement is subjected to error correction to obtain the ground speed of the manned submersible:
Figure GDA0003475932460000042
ocean current velocity at the depth cell where the manned submersible is located:
Figure GDA0003475932460000043
as a further improvement of the present invention, the step S1.3 specifically comprises the following steps:
s1.3.1: selecting a GPS position error, a speed error, an attitude angle error, a gyroscope constant drift error, a gyroscope first-order Markov drift error and an accelerometer first-order Markov drift error as measurement variables, wherein a state variable X is expressed as follows:
X＝[δp δν φ εb εT ▽b]T (10)
δp＝[δL δλ δh]indicating the position error, δ v ═ δ vN δνE δνD]Indicates a speed error, phi ═ phiN φEφD]Representing the attitude angle error, εb＝[εx b εy b εz b]Representing the gyro constant drift error, epsilonT＝[εx T εy T εz T]And +b＝[▽x ▽y ▽z]Respectively, the first order markov drift errors of the gyroscope and the accelerometer, and the obtained state equation is as follows:
Figure GDA0003475932460000044
wherein, the state transition matrix F is:
Figure GDA0003475932460000045
s1.3.2: taking the difference between the position and the speed of the SINS and the GPS as the measurement information of the system, the measurement equation of the SINS/GPS system is as follows:
Figure GDA0003475932460000046
in the formula, VkFor Gaussian white noise, the H matrix is as follows:
Figure GDA0003475932460000047
obtaining a discretized Kalman filtering state equation and a measuring equation according to an error propagation equation solved by SINS and the obtained position and speed information:
Xk+1＝Φk+1∣kXk+Γk+1∣kW k(15)
Zk+1＝HkXk+Vk(16)
wherein, XkFor state estimation at time k, Xk+1For state estimation at time k +1, Zk+1Is an observed value at time k +1, phik+1∣kFor one-step transition matrices of nonsingular states, HkTo observe the matrix, WkIs a systematic random process noise sequence, VkIs a system random measurement noise sequence;
obtaining a Kalman filtering equation according to the state equation and the observation equation:
the state is further predicted:
Figure GDA0003475932460000051
one-step prediction error variance matrix:
Figure GDA0003475932460000052
filter gain momentArraying:
Figure GDA0003475932460000053
and (3) state estimation:
Figure GDA0003475932460000054
estimating an error variance matrix:
Figure GDA0003475932460000055
wherein I represents an identity matrix;
s1.3.3: and (3) correcting the navigation parameters output by the SINS by using the state estimation obtained in the step 1.3.2, wherein the speed v is taken as an example:
Figure GDA0003475932460000056
wherein the content of the first and second substances,
Figure GDA0003475932460000057
and outputting a result for the SINS, wherein delta v is a Kalman filtering estimation result, and v represents an SINS/GPS integrated navigation output result.
As a further improvement of the invention, in step 2, in convection mode, the method of deriving speed and water velocity of the manned vehicle using overlapping ADCP measurements is as follows:
s2.1: the scanning range of the ADCP (from the water surface to the deep sea) is artificially divided into a plurality of depth unit layers with the same depth, the depth from the sea surface to the sea bottom is set to be h meters, the scanning range of the ADCP is Q meters, and the depth of the depth unit layers is set to be Q meters, so that the ADCP can measure the speed of the manned submersible relative to the water flow in K-Q/Q depth unit layers each time
Figure GDA0003475932460000058
S2.2: as can be seen from S1.3 of step 1, GPS can measure the ground speed v of the manned submersible vehicle at the first depth unit layerb(bin1) Working according to ADCPAccording to the principle, the speed of the manned submersible relative to the water flow in K depth unit layers in the scanning range can be measured
Figure GDA0003475932460000059
At this point, v in the first depth cell layer is knownb(bin1) And
Figure GDA00034759324600000510
according to the ground speed expression of the manned submersible under the carrier coordinate system:
Figure GDA00034759324600000511
can be pushed out
Figure GDA00034759324600000512
Thereby solving for the water velocity in the depth cell layer 1
Figure GDA00034759324600000513
S2.3: when the manned submersible vehicle submerges to the 2 nd depth unit layer, the ADCP second scanning range is changed into 2 to (K +1) depth unit layers, and the relative water flow speed of the manned submersible vehicle of the 2 to (K +1) depth unit layers can be measured
Figure GDA00034759324600000514
Wherein ADCP is observed repeatedly in depth units of 2-K;
s2.4: assuming that the ocean current velocities within a certain limit are approximately the same, i.e. the current velocity during the submergence from the first depth cell to the 2 nd depth cell
Figure GDA0003475932460000061
Is not changed according to
Figure GDA0003475932460000062
Can obtain
Figure GDA0003475932460000063
So that there are
Figure GDA0003475932460000064
Wherein the content of the first and second substances,
Figure GDA0003475932460000065
and
Figure GDA0003475932460000066
a second measurement and a first measurement respectively representing overlapping depth cells, the overlapping depth cells of the second and first measurements being 2-K, wherein
Figure GDA0003475932460000067
From formula (6) by vb(bin1) And the error value of the depth cell of two overlapping measurements
Figure GDA0003475932460000068
Finding vb(bin2) From step 2.3, known
Figure GDA0003475932460000069
And is formed by
Figure GDA00034759324600000610
Obtaining
Figure GDA00034759324600000611
S2.5: the manned submersible continues to dive, the scanning times are continuously accumulated in the process, the step S2.3 and the step S2.4 are repeatedly executed from 2-K to 3 (K +1) and 4 (K +2) … of the overlapped depth units, and the ground speed of the manned submersible of all the depth units is obtained
Figure GDA00034759324600000612
And velocity of water flow
Figure GDA00034759324600000613
Has the advantages that: compared with the prior art, the technical scheme of the invention has the following beneficial technical effects:
1. the invention utilizes the measurement of ADCP superposition to deduce the ground speed and the water flow speed of the manned submersible, thereby not only obtaining the ground speed in the submerging/floating process of the carrier, but also obtaining the water flow speed profiles of different depths, and realizing the speed measurement function of the ADCP without a posture sensor.
2. The speed estimation and correction algorithm provided by the invention can effectively compensate the ground speed and the ocean current speed of the manned submersible deduced by adopting ADCP overlapping measurement, so that the speed information is accurate and reliable, and important information support can be provided for scientific investigation, underwater combat and the like.
Drawings
FIG. 1 is a schematic diagram of ADCP speed estimation according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of error correction according to an embodiment of the present invention;
fig. 3 is an abstract attached drawing of the invention.
Detailed Description
The invention is described in further detail below with reference to the following detailed description and accompanying drawings:
the invention provides an ADCP (adaptive Doppler Current profiler) speed estimation and correction algorithm for a deep submersible vehicle. Aiming at the current situation that GPS and DVL can not directly measure the speed of the carrier to the ground and the speed of the ocean current in the diving process of a deep sea area, the invention provides the speed of the manned submersible vehicle to the ground at the initial moment through GPS/SINS combined navigation, then utilizes the ADCP of the deep submersible manned submersible vehicle to estimate the speed of the carrier to the ground and the speed of the ocean current, and solves the problem that the estimation error is accumulated along with the diving depth based on the speed.
Under the condition of not considering an acoustic positioning system, the ground speed of the manned submersible at the initial submergence moment is provided through SINS/GPS combined navigation, then the speed of the manned submersible relative to water flow is measured through an ADCP arranged at the bottom of the manned submersible, and the ground speed and water flow speed profiles of different depths are deduced by further utilizing overlapped ADCP measurement; further acquiring the ground speed of the manned submersible according to the bottom tracking function; finally, the earth velocity and the ocean current velocity in different depth units obtained by adopting ADCP derivation of overlapped measurement in the submergence process of the manned submersible are effectively and accurately corrected through the speed error correction method.
Step 1: ground speed v of manned submersible at diving initial moment is provided through SINS/GPS combined navigationbAs the basis for the estimation of the ocean current velocity at the depth cell level where the ADCP is first measured.
Step 1.1: an SINS navigation resolving algorithm is adopted, an inertial measurement unit outputs angular velocity and specific force information, and navigation information, namely attitude, velocity and position, is output through solving of an inertial navigation mechanical arrangement equation; the navigation resolving equation under the navigation coordinate system is as follows:
Figure GDA0003475932460000071
Figure GDA0003475932460000072
Figure GDA0003475932460000073
selecting a local geographic coordinate system as a navigation coordinate system n, wherein the local geographic coordinate system is a coordinate system of 'northeast land'; a carrier coordinate system b is a front right lower coordinate system; the inertia and earth coordinate systems are respectively marked as i and e,
Figure GDA0003475932460000074
representing a posture matrix from a carrier coordinate system to a navigation coordinate system;
Figure GDA0003475932460000075
the angular rate of the carrier coordinate system relative to the navigation coordinate system is projected under the carrier coordinate system, and the angular rate of the earth coordinate system relative to the inertial coordinate system is projected under the navigation coordinate systemProjecting the angular rate of the navigation coordinate system relative to the terrestrial coordinate system under the navigation coordinate system; vnRepresenting a projection of the ground speed in a navigation coordinate system;
Figure GDA0003475932460000076
specific force information representing an accelerometer output; gnRepresenting the projection of the gravity acceleration under the n system; l, lambda and h respectively represent latitude, longitude and altitude; rn、ReRespectively representing the curvature radius of the earth meridian circle and the Mao-unitary circle;
step 1.2: the GPS navigation is used for resolving, and the speed and the position of the carrier can be measured based on the distance between the measuring station and the satellite:
Figure GDA0003475932460000077
in the formula, Xj、Yj、ZjIs the satellite position, the carrier position Xu、Yu、ZuDetected in real time by the GPS; c is the propagation velocity of the electromagnetic wave;
Figure GDA0003475932460000078
the deviation of the signal receiver clock relative to the GPS time system;
Figure GDA0003475932460000079
the deviation of the kth GPS satellite clock relative to the GPS time system;
Figure GDA00034759324600000710
respectively, the distance deviations caused by the ionosphere and the troposphere;
according to the relationship between the speed and the distance change rate, a three-dimensional speed expression is obtained as follows:
Figure GDA00034759324600000711
the GPS receiver can measure the station satellite distance rhojAnd rate of change thereof
Figure GDA00034759324600000712
Figure GDA0003475932460000081
When the positioning calculation is carried out, the formula (5) only has four unknown numbers, and the speed of the carrier
Figure GDA0003475932460000082
And
Figure GDA0003475932460000083
all unknowns can be solved as long as 4 satellites are measured.
Figure GDA0003475932460000084
In the formula
Figure GDA0003475932460000085
Finally, the three-dimensional speed v of the carrier can be solved according to four equationsnAnd location information.
Step 1.3: on the sea surface, when the GPS works normally, the difference between the position and the speed of the SINS and the GPS is used as measurement information and sent into a Kalman filter, a discretized Kalman filtering equation and a measurement equation are obtained, the SINS error is corrected, and more accurate and reliable navigation information is output.
The specific method comprises the following steps:
step 1.3.1: selecting a GPS position error, a speed error, an attitude angle error, a gyroscope constant drift error, a gyroscope first-order Markov drift error and an accelerometer first-order Markov drift error as measurement variables, wherein a state variable X is expressed as follows:
X＝[δp δν φ εb εT ▽b]T (9)
δp＝[δL δλ δh]indicating the position error, δ v ═ δ vN δνE δνD]Indicates a speed error, phi ═ phiN φEφD]Representing the attitude angle error, εb＝[εx b εy b εz b]Representing the gyro constant drift error, epsilonT＝[εx T εy T εz T]And +b＝[▽x ▽y ▽z]The first order markov drift errors of the gyroscope and the accelerometer respectively. The equation of state is obtained as follows:
Figure GDA0003475932460000086
wherein, the state transition matrix F is:
Figure GDA0003475932460000087
step 1.3.2: taking the difference between the position and the speed of the SINS and the GPS as the measurement information of the system, the measurement equation of the SINS/GPS system is as follows:
Figure GDA0003475932460000088
in the formula, VkFor Gaussian white noise, the H matrix is as follows:
Figure GDA0003475932460000091
obtaining a discretized Kalman filtering state equation and a measuring equation according to an error propagation equation solved by SINS and the obtained position and speed information:
Xk+1＝Φk+1∣kXk+Γk+1∣kWk (14)
Zk+1＝HkXk+Vk (15)
wherein, XkFor state estimation at time k, Xk+1For state estimation at time k +1, Zk+1Is an observed value at time k +1, phik+1∣kFor one-step transition matrices of nonsingular states, HkTo observe the matrix, WkIs a systematic random process noise sequence, VkIs a system random measurement noise sequence;
obtaining a Kalman filtering equation according to the state equation and the observation equation:
the state is further predicted:
Figure GDA0003475932460000092
one-step prediction error variance matrix:
Figure GDA0003475932460000093
a filter gain matrix:
Figure GDA0003475932460000094
and (3) state estimation:
Figure GDA0003475932460000095
estimating an error variance matrix:
Figure GDA0003475932460000096
wherein I represents an identity matrix.
Step 1.3.3: and (3) correcting the navigation parameters output by the SINS by using the state estimation obtained in the step 1.3.2, wherein the speed v is taken as an example:
Figure GDA0003475932460000097
wherein the content of the first and second substances,
Figure GDA0003475932460000098
and outputting a result for the SINS, wherein delta v is a Kalman filtering estimation result, and v represents an SINS/GPS integrated navigation output result.
Step 1.4: provided according to SINS/GPS integrated navigation solution
Figure GDA0003475932460000099
νnAnd the information such as the position and the like, and the ground speed v of the manned submersible at the initial moment is obtained by the following formulab：
Figure GDA00034759324600000910
Step 2: an acoustic Doppler velocimeter (ADCP) mounted at the bottom of the manned submersible is used for measuring the speed of the manned submersible relative to water flow in the diving process, and the earth speed and the water flow speed of the manned submersible are derived by using repeated measurement in continuous ADCP scanning:
Figure GDA00034759324600000911
wherein the content of the first and second substances,
Figure GDA00034759324600000912
representing the relative water flow velocity of the manned submersible,
Figure GDA00034759324600000913
indicating the water flow rate.
Step 2.1: measuring relative water velocity of manned submersible by ADCP
Figure GDA00034759324600000914
Fig. 1 is a diagram of ADCP velocity measurement, the ADCP is installed right under the submersible, and a JANUS beam structure (consisting of 4 transducers) is used, as shown in fig. 1: in an embodiment the emitted sound line of each transducer is at a 30 ° projection angle to the profiler axis. The working process of speed measurement is as follows: firstly, transmitting acoustic signals with certain frequency to seawater,because scattering particles exist in the water body, a part of scattering echo signals are received by the receiving transducer, because Doppler frequency shift exists between the frequency of the transmitted sound waves and the frequency of the scattering echo, the relative speed of the beam direction is obtained through frequency shift calculation, and then the relative speed is converted into the speed under a carrier coordinate system through the included angle of the beam direction
Figure GDA00034759324600001024
Step 2.2: and (4) deriving the ground speed and water flow speed profiles of different depths by using repeated measurement of the convection speed of the manned submersible in different scanning operations of the ADCP.
In the examples: as shown in fig. 1, the ADCP scanning range Q is set to 10 meters, and the depth unit layer depth Q is set to 1 meter, so that the range of each ADCP scanning is 10 meters, and the depth of 10 depth unit layers is total. (the numerical settings in the embodiments herein are for illustration only, and the settings can be made in other embodiments as the case may be)
Step 2.2.1: before non-submergence, initializing the first depth unit layer and obtaining vb(bin1)、
Figure GDA0003475932460000101
And
Figure GDA0003475932460000102
assuming that the manned vehicle is at the sea surface and is not submerged, the high-precision Global Positioning System (GPS) can be used to measure the ground speed v of the manned vehicle at the first depth unit layerb(bin1) According to the working principle of ADCP, the speed of the manned submersible relative to the water flow in K depth unit layers in the scanning range can be measured
Figure GDA0003475932460000103
At this point, v in the first depth cell layer is knownb(bin1) And
Figure GDA0003475932460000104
according to the carrierThe system downloads the expression of the speed of the manned submersible vehicle to the ground:
Figure GDA0003475932460000105
can be pushed out
Figure GDA0003475932460000106
Thereby solving for the water velocity in the depth cell layer 1
Figure GDA0003475932460000107
Step 2.2.2: submerge to the 2 nd depth cell layer to obtain
Figure GDA0003475932460000108
When the manned submersible vehicle submerges to the 2 nd depth unit layer, the ADCP second scanning range is changed into 2 to (K +1) depth unit layers, and the relative water flow speed of the manned submersible vehicle of the 2 to (K +1) depth unit layers can be measured
Figure GDA0003475932460000109
Where ADCP repeats for depth units of 2 to K.
Step 2.2.3: v acquisition from repeated measurements in the second and first ADCP scansb(bin2)、
Figure GDA00034759324600001010
Assuming that the ocean current velocities within a certain limit are approximately the same, i.e. the current velocity during the submergence from the first depth cell to the 2 nd depth cell
Figure GDA00034759324600001011
Is not changed according to
Figure GDA00034759324600001012
Can obtain
Figure GDA00034759324600001013
So that there are
Figure GDA00034759324600001014
Wherein the content of the first and second substances,
Figure GDA00034759324600001015
and
Figure GDA00034759324600001016
a second measurement and a first measurement respectively representing overlapping depth cells, the overlapping depth cells of the second and first measurements being 2-K, wherein
Figure GDA00034759324600001017
From formula (6) by vb(bin1) And the error value of the depth cell of two overlapping measurements
Figure GDA00034759324600001018
Finding vb(bin2) From step 2.4, known
Figure GDA00034759324600001019
And is formed by
Figure GDA00034759324600001020
To obtain
Figure GDA00034759324600001021
Step 2.2.4: the manned submersible continues to dive, the scanning times are continuously accumulated in the process, the manned submersible sequentially iterates, the operation of the step 2.2.2 and the operation of the step 2.2.3 are repeated, and the ground speed of the manned submersible of all the depth units is obtained
Figure GDA00034759324600001022
And velocity of water flow
Figure GDA00034759324600001023
And step 3: the manned submersible submerges to the near seabed, the ground speed of the manned submersible can be directly obtained by using the ADCP bottom tracking function, error comparison is further carried out on the ground speed of the manned submersible and the previously overlapped ADCP measurement, and the ground speed and the water flow speed of unit layers with different depths are corrected based on the linear relation that the estimation error is in direct proportion to the submerging depth. The specific method comprises the following steps:
step 3.1: the ADCP uses a bottom tracking method to obtain the ground speed of the manned submersible.
FIG. 3 is an ADCP bottom tracking velocity chart, as shown in FIG. 3, when the deep submersible vehicle reaches the near sea bottom, the bottom tracking method can be used to make the reflection of the sea bottom to the signal obtain the echo signal, and the velocity v to the ground of the submersible vehicle can be obtained by calculating the Doppler frequency shift of the reflected signalb(track) thereby obtaining the ocean current velocity of the depth cell
Figure GDA0003475932460000111
Step 3.2: and (3) making a difference between the ground speed and the water flow speed of the manned submersible deduced in the step (2) and the ground speed and the ocean current speed obtained in the step (3.1).
The ground speed v of the manned vehicle will be derived using the overlapped ADCP measurementsb(binn) And the ground speed v of the manned submersible acquired by using the ADCP bottom tracking methodb(trackn) Performing difference making to obtain the error delta v of the ground speed of estimation and measurementb(n); the ocean current velocity derived from the overlapped ADCP measurement is also differed from the ocean current velocity calculated under the bottom tracking method
Figure GDA0003475932460000112
Step 3.3: and (3) carrying out error correction on the speed information deduced by the superposition of the ADCP multiple scanning in the step 2 by utilizing the ground speed of the manned submersible acquired by the ADCP bottom tracking method and the ocean current speed calculated by the ground speed.
According to the characteristic that the estimation error of the manned submersible and the ocean current velocity is linear with the submergence time and the depth, the initial submergence time is assumedThe depth of the offshore platform is h meters, the depth of each unit of the ADCP is d meters, and the total number of the depth units is N h/d, which are sequentially ordered (the earth and ocean current speed of each layer of the depth units can be obtained by step 2). The error of the ground speed of the manned submersible in each layer of depth unit is delta vb(n)＝(δνb(n)/n)·binn(ii) a An ocean current velocity error of
Figure GDA0003475932460000113
Since the ground speed of the first floor depth cell can be solved by the navigation system, no overlap ADCP measurement estimation is needed, so n > 1.
By the error estimation method, the speed error of each layer of depth unit is taken as a reference, and the speed derived by the overlapped ADCP measurement is subjected to error correction:
correcting the ground speed error of the manned submersible:
Figure GDA0003475932460000114
correcting the ocean current speed error at the depth unit where the manned submersible is located:
Figure GDA0003475932460000115
in the present invention, on the one hand, the ground speed and water velocity information of the manned submersible can be estimated using the measurements of the overlay ADCP; on the other hand, the previously estimated speed information can be corrected by using the speed information measured by the bottom tracking function of the ADCP, and other sensors do not need to be additionally equipped.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, but any modifications or equivalent variations made according to the technical spirit of the present invention are within the scope of the present invention as claimed.

Claims (3)

1. An ADCP speed estimation and correction algorithm for a deep submersible manned submersible is characterized by comprising the following specific steps:
(1) on the sea surface, the ground speed v of the manned submersible at the initial moment is provided by using SINS/GPS combined navigationb；
The method for providing the ground speed of the manned submersible at the initial moment through the SINS/GPS integrated navigation in the step (1) comprises the following steps:
s1.1: an SINS navigation resolving algorithm is adopted, an inertial measurement unit outputs angular velocity and specific force information, and navigation information, namely attitude, velocity and position, is output through solving of an inertial navigation mechanical arrangement equation; the navigation resolving equation under the navigation coordinate system is as follows:
Figure FDA0003475932450000011
Figure FDA0003475932450000012
Figure FDA0003475932450000013
selecting a local geographic coordinate system as a navigation coordinate system n, wherein the local geographic coordinate system is a coordinate system of 'northeast land'; a carrier coordinate system b is a front right lower coordinate system; the inertia and earth coordinate systems are respectively marked as i and e,
Figure FDA0003475932450000014
representing a posture matrix from a carrier coordinate system to a navigation coordinate system;
Figure FDA0003475932450000015
the angular rate of the carrier coordinate system relative to the navigation coordinate system is projected under the carrier coordinate system, the angular rate of the earth coordinate system relative to the inertial coordinate system is projected under the navigation coordinate system, and the angular rate of the navigation coordinate system relative to the earth coordinate system is projected under the navigation coordinate system; vnRepresenting a projection of the ground speed in a navigation coordinate system;
Figure FDA0003475932450000016
specific force information representing an accelerometer output; gnRepresenting the projection of the gravity acceleration under the n system; l, lambda and h respectively represent latitude, longitude and altitude; rn、ReRespectively representing the curvature radius of the earth meridian circle and the Mao-unitary circle;
s1.2: the GPS navigation is used for resolving, and the speed and the position of the carrier can be measured based on the distance between the measuring station and the satellite:
Figure FDA0003475932450000017
in the formula, Xj、Yj、ZjIs the satellite position, the carrier position Xu、Yu、ZuDetected in real time by the GPS; c is the propagation velocity of the electromagnetic wave;
Figure FDA0003475932450000018
the deviation of the signal receiver clock relative to the GPS time system;
Figure FDA0003475932450000019
the deviation of the kth GPS satellite clock relative to the GPS time system;
Figure FDA00034759324500000110
respectively, the distance deviations caused by the ionosphere and the troposphere;
according to the relationship between the speed and the distance change rate, a three-dimensional speed expression is obtained as follows:
Figure FDA00034759324500000111
the GPS receiver can measure the station satellite distance rhojAnd rate of change thereof
Figure FDA00034759324500000112
Figure FDA00034759324500000113
When the positioning calculation is carried out, the formula (5) only has four unknown numbers, and the speed of the carrier
Figure FDA00034759324500000114
And
Figure FDA00034759324500000115
all unknowns can be solved as long as 4 satellites are measured;
Figure FDA0003475932450000021
in the formula
Figure FDA0003475932450000022
Finally, the three-dimensional speed v of the carrier can be solved according to four equationsnAnd location information;
s1.3: on the sea surface, when the GPS works normally, the difference between the position and the speed of the SINS and the GPS is used as measurement information and sent into a Kalman filter to obtain a discretized Kalman filtering equation and a measurement equation, the SINS error is corrected, and more accurate and reliable navigation information is output;
s1.4: provided according to SINS/GPS
Figure FDA0003475932450000023
VnAnd position (L, lambda, h) information, and the ground speed V of the manned submersible at the initial moment is obtained by the following formulab；
Figure FDA0003475932450000024
(2) ADCP operating in convection mode, measuring the relative current velocity of the manned vehicle
Figure FDA0003475932450000025
Deducing the ground speed v of a manned submersible by repeated measurement of multiple ADCP scansbAnd velocity of water flow
Figure FDA0003475932450000026
In the step (2), the convection velocity of the manned submersible is measured through ADCP: ADCP firstly transmits sound wave signals with certain frequency to seawater, because scattering particles exist in the water, a part of scattering echo signals are received by a receiving transducer, because Doppler frequency shift exists between the transmitted sound wave and the scattering echo frequencies, the relative speed of the wave beam direction is obtained through frequency shift calculation, and then the wave beam direction is converted into the speed under a carrier coordinate system through the included angle of the wave beam direction
Figure FDA0003475932450000027
(3) Submerging to the offshore bottom, deducing the error of the ground speed of the manned submersible by using the ground speed of the manned submersible obtained by the ADCP bottom tracking function and the overlapped ADCP measurement, and providing a method for realizing error correction on the ground speed and the water flow speed of the manned submersible in each depth unit layer;
submerging to the near seabed in the step (3), deducing the error of the ground speed of the manned submersible by using the ground speed of the manned submersible obtained by the ADCP bottom tracking function and the overlapped ADCP measurement, and realizing the error correction of the ground speed and the water flow speed of the manned submersible in each depth unit layer as follows:
s3.1: when the deep submergence manned submersible reaches the near seabed, the bottom tracking method can be used to enable the seabed to reflect the signal to obtain an echo signal, and the Doppler frequency of the reflected signal is usedCalculating to obtain the ground speed v of manned submersibleb(track) thereby obtaining the ocean current velocity of the depth cell
Figure FDA0003475932450000028
S3.2: the ground speed v of the manned vehicle will be derived using the overlapped ADCP measurementsb(binN) And the ground speed v of the manned submersible acquired by using the ADCP bottom tracking methodb(trackN) Performing difference making to obtain the error delta v of the ground speed of estimation and measurementb(N); the ocean current velocity derived from the overlapped ADCP measurement is also differed from the ocean current velocity calculated under the bottom tracking method
Figure FDA0003475932450000029
S3.3: according to the characteristic that estimation errors of the manned submersible vehicle and the ocean current speed are in linear relation with the submergence time and the depth, the depth from the initial submergence time to the offshore bottom is assumed to be h meters, the depths of all units of ADCP are known to be d meters, the total number of depth units is N-h/d, the units are sequentially sequenced, the earth and ocean current speeds of each layer of depth unit are known according to the step 2, and the error of the earth speed of the manned submersible vehicle in each layer of depth unit is delta vb(n)＝(δνb(N)/N)·binn(ii) a An ocean current velocity error of
Figure FDA0003475932450000031
Since the ground speed of the first layer depth cell can be solved by the navigation system, no overlapped ADCP measurement estimation is needed, so n > 1;
s3.4: by the error estimation method, the speed error of each layer of depth unit is taken as a reference, and the speed deduced by the overlapped ADCP measurement is subjected to error correction to obtain the ground speed of the manned submersible:
Figure FDA0003475932450000032
ocean current velocity at the depth cell where the manned submersible is located:
Figure FDA0003475932450000033
2. the ADCP speed estimation and correction algorithm for a deep submergence manned vehicle according to claim 1, wherein the step S1.3 comprises the following steps:
s1.3.1: selecting a GPS position error, a speed error, an attitude angle error, a gyroscope constant drift error, a gyroscope first-order Markov drift error and an accelerometer first-order Markov drift error as measurement variables, wherein a state variable X is expressed as follows:
X＝[δp δν φ εb εT ▽b]T (10)
δp＝[δL δλ δh]indicating the position error, δ v ═ δ vN δνE δνD]Indicates a speed error, phi ═ phiN φE φD]Representing the attitude angle error, εb＝[εx b εy b εz b]Representing the gyro constant drift error, epsilonT＝[εx T εy T εz T]And +b＝[▽x ▽y ▽z]Respectively, the first order markov drift errors of the gyroscope and the accelerometer, and the obtained state equation is as follows:
Figure FDA0003475932450000034
wherein, the state transition matrix F is:
Figure FDA0003475932450000035
s1.3.2: taking the difference between the position and the speed of the SINS and the GPS as the measurement information of the system, the measurement equation of the SINS/GPS system is as follows:
Figure FDA0003475932450000036
in the formula, VkFor Gaussian white noise, the H matrix is as follows:
Figure FDA0003475932450000041
obtaining a discretized Kalman filtering state equation and a measuring equation according to an error propagation equation solved by SINS and the obtained position and speed information:
Xk+1＝Φk+1∣kXk+Γk+1∣kWk(15)
Zk+1＝HkXk+Vk(16)
wherein, XkFor state estimation at time k, Xk+1For state estimation at time k +1, Zk+1Is an observed value at time k +1, phik+1∣kFor one-step transition matrices of nonsingular states, HkTo observe the matrix, WkIs a systematic random process noise sequence, VkIs a system random measurement noise sequence;
obtaining a Kalman filtering equation according to the state equation and the observation equation:
and (3) state prediction:
Figure FDA0003475932450000042
one-step prediction error variance matrix:
Figure FDA0003475932450000043
a filter gain matrix:
Figure FDA0003475932450000044
and (3) state estimation:
Figure FDA0003475932450000045
estimating an error variance matrix:
Figure FDA0003475932450000046
wherein I represents an identity matrix;
s1.3.3: and (3) correcting the navigation parameters output by the SINS by using the state estimation obtained in the step 1.3.2, wherein the speed v is taken as an example:
Figure FDA0003475932450000047
wherein the content of the first and second substances,
Figure FDA0003475932450000048
and outputting a result for the SINS, wherein delta v is a Kalman filtering estimation result, and v represents an SINS/GPS integrated navigation output result.
3. An ADCP speed estimation and correction algorithm for a deep submergence manned vehicle according to claim 1, wherein in the step (2) in convection mode, the method of deriving speed and water velocity of the manned vehicle using overlapping ADCP measurements is as follows:
s2.1: the scanning range of the ADCP is artificially divided into a plurality of depth unit layers with the same depth from the water surface to the deep ocean, the depth from the sea surface to the sea bottom is set to be h meters, the scanning range of the ADCP is Q meters, and the depth of the depth unit layers is set to be Q meters, so that the ADCP can measure the speed of the manned submersible relative to the water flow in K-Q/Q depth unit layers each time
Figure FDA0003475932450000049
S2.2: as can be seen from S1.3 of step 1, GPS can measure the ground speed v of the manned submersible vehicle at the first depth unit layerb(bin1) According to the working principle of ADCP, the speed of the manned submersible relative to the water flow in K depth unit layers in the scanning range can be measured
Figure FDA0003475932450000051
At this point, v in the first depth cell layer is knownb(bin1) And
Figure FDA0003475932450000052
according to the ground speed expression of the manned submersible under the carrier coordinate system:
Figure FDA0003475932450000053
can be pushed out
Figure FDA0003475932450000054
Thereby solving for the water velocity in the depth cell layer 1
Figure FDA0003475932450000055
S2.3: when the manned submersible vehicle submerges to the 2 nd depth unit layer, the ADCP second scanning range is changed into 2 to (K +1) depth unit layers, and the relative water flow speed of the manned submersible vehicle of the 2 to (K +1) depth unit layers can be measured
Figure FDA0003475932450000056
Wherein ADCP is observed repeatedly in depth units of 2-K;
s2.4: assuming that the ocean current velocities within a certain limit are approximately the same, i.e. the current velocity during the submergence from the first depth cell to the 2 nd depth cell
Figure FDA0003475932450000057
Is not changed according to
Figure FDA0003475932450000058
Can obtain
Figure FDA0003475932450000059
So that there are
Figure FDA00034759324500000510
Wherein the content of the first and second substances,
Figure FDA00034759324500000511
and
Figure FDA00034759324500000512
a second measurement and a first measurement respectively representing overlapping depth cells, the overlapping depth cells of the second and first measurements being 2-K, wherein
Figure FDA00034759324500000513
From formula (6) by vb(bin1) And the error value of the depth cell of two overlapping measurements
Figure FDA00034759324500000514
Finding vb(bin2) From step 2.3, known
Figure FDA00034759324500000515
And is formed by
Figure FDA00034759324500000516
Obtaining
Figure FDA00034759324500000517
S2.5: the manned submersible continues to dive, the scanning times are continuously accumulated in the process, the step S2.3 and the step S2.4 are repeatedly executed from 2-K to 3 (K +1) and 4 (K +2) … of the overlapped depth units, and the ground speed of the manned submersible of all the depth units is obtained
Figure FDA00034759324500000518
And velocity of water flow
Figure FDA00034759324500000519
CN202011491308.2A 2020-12-17 2020-12-17 ADCP (advanced digital control Performance) speed estimation and correction algorithm for deep submersible vehicle Active CN112684207B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202011491308.2A CN112684207B (en) 2020-12-17 2020-12-17 ADCP (advanced digital control Performance) speed estimation and correction algorithm for deep submersible vehicle

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202011491308.2A CN112684207B (en) 2020-12-17 2020-12-17 ADCP (advanced digital control Performance) speed estimation and correction algorithm for deep submersible vehicle

Publications (2)

Publication Number Publication Date
CN112684207A CN112684207A (en) 2021-04-20
CN112684207B true CN112684207B (en) 2022-03-11

Family

ID=75448513

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202011491308.2A Active CN112684207B (en) 2020-12-17 2020-12-17 ADCP (advanced digital control Performance) speed estimation and correction algorithm for deep submersible vehicle

Country Status (1)

Country Link
CN (1) CN112684207B (en)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114236173B (en) * 2021-12-16 2024-04-02 中国人民解放军国防科技大学 Ocean current velocity estimation method based on SINS and GNSS combination and DVL
CN114578092B (en) * 2022-01-12 2023-06-09 华东师范大学 Dynamic bottom error correction method for bottom tracking speed of acoustic Doppler flow velocity profiler
CN115979260B (en) * 2023-02-24 2023-06-02 北京大学 Bionic navigation system, method, equipment and computer storage medium

Citations (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2000111375A (en) * 1998-10-06 2000-04-18 Kansai Electric Power Co Inc:The Devices for continuously observing flow rate, turbidity of water, and hydraulic information
CN104870940A (en) * 2012-10-29 2015-08-26 德立文亚迪仪器公司 System and method for water column aided navigation
CN104965102A (en) * 2015-05-25 2015-10-07 厦门大学 Method of effectively improving flow direction measurement precision of acoustic doppler current profiler
CN105824036A (en) * 2014-10-31 2016-08-03 波音公司 Position-locking for a watercraft using an auxiliary water vessel
CN105841717A (en) * 2016-06-07 2016-08-10 哈尔滨工业大学 Rapid correction method for course error of strapdown inertial navigation system
KR101868096B1 (en) * 2017-09-27 2018-07-17 엘아이지넥스원 주식회사 Apparatus and method for performance verification test of inertial measurement unit
CN109141436A (en) * 2018-09-30 2019-01-04 东南大学 The improved Unscented kalman filtering algorithm application method in integrated navigation under water
CN109443379A (en) * 2018-09-28 2019-03-08 东南大学 A kind of underwater anti-shake dynamic alignment methods of the SINS/DVL of deep-sea submariner device
CN109612460A (en) * 2018-12-19 2019-04-12 东南大学 One kind being based on static modified deviation of plumb line measurement method
KR20190074428A (en) * 2017-12-20 2019-06-28 한국해양과학기술원 Apparatus For Heading Information Estimating And Correcting Of Remote Operated Vehicle And Method For Heading Information Estimating And Correcting Of Remote Operated Vehicle In Using Same
CN110044378A (en) * 2019-04-17 2019-07-23 河海大学 A kind of fiber strapdown inertial navigation high-accuracy position system and method for underwater bathyscaph
CN110095117A (en) * 2019-05-15 2019-08-06 南京理工大学 A kind of air navigation aid that gyro free inertia measurement system is combined with GPS
CN110274591A (en) * 2019-06-20 2019-09-24 东南大学 Deep diving manned underwater vehicle ADCP assists SINS air navigation aid
CN110345941A (en) * 2019-06-13 2019-10-18 东南大学 Deep diving manned underwater vehicle SINS is from auxiliary navigation method
CN111076728A (en) * 2020-01-13 2020-04-28 东南大学 DR/USBL-based deep submersible vehicle combined navigation method

Patent Citations (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2000111375A (en) * 1998-10-06 2000-04-18 Kansai Electric Power Co Inc:The Devices for continuously observing flow rate, turbidity of water, and hydraulic information
CN104870940A (en) * 2012-10-29 2015-08-26 德立文亚迪仪器公司 System and method for water column aided navigation
CN105824036A (en) * 2014-10-31 2016-08-03 波音公司 Position-locking for a watercraft using an auxiliary water vessel
CN104965102A (en) * 2015-05-25 2015-10-07 厦门大学 Method of effectively improving flow direction measurement precision of acoustic doppler current profiler
CN105841717A (en) * 2016-06-07 2016-08-10 哈尔滨工业大学 Rapid correction method for course error of strapdown inertial navigation system
KR101868096B1 (en) * 2017-09-27 2018-07-17 엘아이지넥스원 주식회사 Apparatus and method for performance verification test of inertial measurement unit
KR20190074428A (en) * 2017-12-20 2019-06-28 한국해양과학기술원 Apparatus For Heading Information Estimating And Correcting Of Remote Operated Vehicle And Method For Heading Information Estimating And Correcting Of Remote Operated Vehicle In Using Same
CN109443379A (en) * 2018-09-28 2019-03-08 东南大学 A kind of underwater anti-shake dynamic alignment methods of the SINS/DVL of deep-sea submariner device
CN109141436A (en) * 2018-09-30 2019-01-04 东南大学 The improved Unscented kalman filtering algorithm application method in integrated navigation under water
CN109612460A (en) * 2018-12-19 2019-04-12 东南大学 One kind being based on static modified deviation of plumb line measurement method
CN110044378A (en) * 2019-04-17 2019-07-23 河海大学 A kind of fiber strapdown inertial navigation high-accuracy position system and method for underwater bathyscaph
CN110095117A (en) * 2019-05-15 2019-08-06 南京理工大学 A kind of air navigation aid that gyro free inertia measurement system is combined with GPS
CN110345941A (en) * 2019-06-13 2019-10-18 东南大学 Deep diving manned underwater vehicle SINS is from auxiliary navigation method
CN110274591A (en) * 2019-06-20 2019-09-24 东南大学 Deep diving manned underwater vehicle ADCP assists SINS air navigation aid
CN111076728A (en) * 2020-01-13 2020-04-28 东南大学 DR/USBL-based deep submersible vehicle combined navigation method

Non-Patent Citations (9)

* Cited by examiner, † Cited by third party
Title
《A Tightly Integrated SINS/DVL Navigation Method for Autonomous Underwater Vehicle》;Zhang Yonggang;《2013 International Conference on Computational and Information Sciences》;20130623;全文 *
《Application of Neural Network-Assisted GNSS/SINS CalibrationSystem in UUV》;Zhihao Liu;《2019 IEEE 3rd Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)》;20191013;全文 *
《Estimation of high-resolution sediment concentration profiles in bottom boundary layer using pulse-coherent acoustic Doppler current profilers》;H. K. Ha;《Marine Geology》;20110111;全文 *
《Initial Alignment for a Doppler Velocity Log-Aided Strapdown Inertial Navigation System With Limited Information》;Lubin Chang;《IEEE/ASME Transactions on Mechatronics》;20161111;全文 *
《In-motion coarse alignment method for SINS/DVL with the attitude dynamics》;Yiqing Yao;《ISA Transactions》;20200527;全文 *
《SINS/DVL 组合导航技术综述》;王博;《导航定位学报》;20200615;全文 *
《SINS/DVL组合导航技术研究》;吕召鹏;《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》;20120715;全文 *
《基于单信标测距辅助SINS的中层水域导航算法》;刘湘衡;《水下无人系统学报》;20201215;全文 *
《基于多普勒计程仪的SINS/DVL组合导航技术及误差分析》;牛雷;《2019年上海-西安声学学会第六届声学学术交流会议论文集》;20191026;全文 *

Also Published As

Publication number Publication date
CN112684207A (en) 2021-04-20

Similar Documents

Publication Publication Date Title
CN112684207B (en) ADCP (advanced digital control Performance) speed estimation and correction algorithm for deep submersible vehicle
US9372255B2 (en) Determining a position of a submersible vehicle within a body of water
CN104316045B (en) A kind of AUV based on SINS/LBL interacts aided positioning system and localization method under water
CN103744098B (en) AUV integrated navigation systems based on SINS/DVL/GPS
US7139647B2 (en) Methods and systems for navigating under water
CN110121662A (en) Marine GNSS reference station device, sea GNSS positioning system and the method for generating marine positioning reference data
CN110274591B (en) ADCP (advanced deep submersible vehicle) assisted SINS (strapdown inertial navigation system) navigation method of deep submersible manned submersible
CN111896962B (en) Submarine transponder positioning method, system, storage medium and application
CN101900558A (en) Combined navigation method of integrated sonar micro navigation autonomous underwater robot
RU2563332C2 (en) Navigation method for autonomous unmanned underwater vehicle
McPhail et al. Range-only positioning of a deep-diving autonomous underwater vehicle from a surface ship
CN112729291B (en) SINS/DVL ocean current velocity estimation method for deep-submergence long-endurance submersible
CN111829512A (en) AUV navigation positioning method and system based on multi-sensor data fusion
JP2018084445A (en) Underwater acoustic positioning system
CN115390012B (en) Multi-transponder coordinate measuring method, device and system for HOV (Hov) accurate positioning
Hagen et al. Low altitude AUV terrain navigation using an interferometric sidescan sonar
CN117029872A (en) AUV navigation method and system based on INS/DVL/LBL tight combination
RU2555479C2 (en) High-precision coordination of underwater complex for underwater navigation
Busse et al. Assessment of underwater positioning accuracy of acoustic modems using real-time kinematic gnss
CN115930951A (en) Short-term underwater AUV hidden navigation method based on multi-sensor combination
JP3234889B2 (en) Bathymetry system using GPS kinematic positioning method
CN114459476B (en) Underwater unmanned submarine current measuring DVL/SINS integrated navigation method based on virtual speed measurement
Jakuba et al. Performance of a low-power one-way travel-time inverted ultra-short baseline navigation system
Geng et al. A low-cost MEMS IMU/DVL/Pressure Sensor integrated navigation system for autonomous underwater vehicle
Watanabe et al. Conceptual design of navigation of an AUV for Monitoring CCS site at deep sea bottom

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