CN109752698A - A kind of inertial navigation method for estimating error of airborne synthetic aperture radar - Google Patents
A kind of inertial navigation method for estimating error of airborne synthetic aperture radar Download PDFInfo
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- CN109752698A CN109752698A CN201811517418.4A CN201811517418A CN109752698A CN 109752698 A CN109752698 A CN 109752698A CN 201811517418 A CN201811517418 A CN 201811517418A CN 109752698 A CN109752698 A CN 109752698A
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Abstract
The invention discloses a kind of inertial navigation method for estimating error of airborne synthetic aperture radar, are related to airborne synthetic aperture radar field.This method comprises: obtaining the first geographical coordinate of m ground control point respectively；Obtain the echo-signal that airborne synthetic aperture radar detects target area；It is imaged according to m ground control point and echo-signal, obtains m subgraph；The second geographical coordinate of ground control point in each subgraph is extracted respectively, and the position error vector of each ground control point is obtained according to the first geographical coordinate and the second geographical coordinate respectively；Observing matrix is constructed according to the first geographical coordinate of whole ground control points；It estimates to obtain inertial navigation error vector according to whole position error vector sum observing matrixes.Inertial navigation method for estimating error provided by the invention, improves the operation efficiency of inertial navigation estimation error, can obtain high-precision inertial navigation error vector, is suitable for processing in real time.
Description
Technical field
The present invention relates to airborne synthetic aperture radar fields more particularly to a kind of inertia of airborne synthetic aperture radar to lead
Navigate method for estimating error.
Background technique
High precision image positioning is the critical issue that airborne synthetic aperture radar needs to solve, known to landform altitude
Under the conditions of, main framing error is due to caused by the precision deficiency of Airborne Inertial navigation system.Particularly with small-sized
Unmanned aerial vehicle platform is limited by condition, is only equipped with low accuracy inertial navigation system mostly, and it is fixed to be unable to satisfy high-precision image
Position requires.
Current framing calibration means are chiefly used in post processing of image, need to carry out secondary imaging processing correction image
Position error, this method needs to carry out scene thick imaging in advance, therefore operand is big, it is impossible to be used in processing in real time.
Summary of the invention
The technical problem to be solved by the present invention is in view of the deficiencies of the prior art, provide a kind of airbome synthetic aperture thunder
The inertial navigation method for estimating error and a kind of storage medium reached.
The technical scheme to solve the above technical problems is that
A kind of inertial navigation method for estimating error of airborne synthetic aperture radar, comprising:
The first geographical coordinate of m ground control point, m >=3 are obtained respectively；
Obtain the echo-signal that airborne synthetic aperture radar detects target area；
It is imaged according to the m ground control points and the echo-signal, obtains m subgraph；
The second geographical coordinate of ground control point described in each subgraph is extracted respectively, respectively according to described
One geographical coordinate and second geographical coordinate obtain the position error vector of each ground control point；
Observing matrix is constructed according to the first geographical coordinate of all ground control points；
It estimates to obtain the airborne synthetic aperture radar according to observing matrix described in all position error vector sums
Inertial navigation error vector.
The beneficial effects of the present invention are: inertial navigation method for estimating error provided by the invention, by echo-signal into
The imaging of row subgraph, improves the operation efficiency of inertial navigation estimation error, and by calculating separately each ground control point
Position error vector constructs observing matrix, can obtain high-precision inertial navigation error vector, is suitable for processing in real time.
The another technical solution that the present invention solves above-mentioned technical problem is as follows:
A kind of storage medium is stored with instruction in the storage medium, when computer reads described instruction, makes described
Computer executes inertial navigation method for estimating error as described in the above technical scheme.
The advantages of additional aspect of the invention, will be set forth in part in the description, partially will from the following description
Become obvious, or practice is recognized through the invention.
Detailed description of the invention
Fig. 1 is the flow diagram that the embodiment of inertial navigation method for estimating error of the present invention provides；
Fig. 2 is the imaging geometry model schematic that the other embodiments of inertial navigation method for estimating error of the present invention provide
Figure；
Fig. 3 (a)-(f), which is that provide 6 of other embodiments of inertial navigation method for estimating error of the present invention are to be estimated, to be used to
The mean square error comparison diagram of property navigation error；
Fig. 4 is the experiment scene schematic diagram that the other embodiments of inertial navigation method for estimating error of the present invention provide；
Fig. 5 is the corresponding optics of experiment scene that the other embodiments of inertial navigation method for estimating error of the present invention provide
Image schematic diagram；
Fig. 6 is the ground control point quantity that the other embodiments of inertial navigation method for estimating error of the present invention provide and fortune
The variation schematic diagram of evaluation time.
Specific embodiment
The principle and features of the present invention will be described below with reference to the accompanying drawings, and illustrated embodiment is served only for explaining the present invention,
It is not intended to limit the scope of the present invention.
As shown in Figure 1, this is estimated for the flow diagram that provides of embodiment of inertial navigation method for estimating error of the present invention
Calculation method includes:
S1 obtains the first geographical coordinate of m ground control point, m >=3 respectively.
It should be noted that ground control point is chosen in known image scene.
Preferably, 3 ground control points can be chosen, calculating speed can be improved while guaranteeing estimation precision.
S2 obtains the echo-signal that airborne synthetic aperture radar detects target area.
It should be noted that echo-signal is to be detected to obtain within a preset period of time by airborne synthetic aperture radar.
S3 is imaged according to m ground control point and echo-signal, obtains m subgraph.
It should be noted that multiple imaging grids can be established, for echo-signal respectively according to each ground control point
It is imaged, the quantity and size that grid is imaged can be arranged according to actual needs.
S4 extracts the second geographical coordinate of ground control point in each subgraph, respectively according to the first geographical coordinate respectively
The position error vector of each ground control point is obtained with the second geographical coordinate.
For example, the first geographical coordinate and the second geographical coordinate can be subtracted each other, position error vector, this field skill are obtained
Art personnel can also calculation of position errors vector by other means.
S5 constructs observing matrix according to the first geographical coordinate of whole ground control points.
It should be understood that include in observing matrix each ground control point coordinate and carrier aircraft along course movement velocity.
S6 estimates to obtain the inertial navigation of airborne synthetic aperture radar according to whole position error vector sum observing matrixes
Error vector.
For example, object location error observational equation in each subgraph imaging results can be constructed:
G=HL+n
Wherein, G is position error vector, and H is observing matrix, and L is inertial navigation error parameter to be estimated, and n is observation noise
Vector, for assessing inertial navigation error, L can be indicated observation noise vector n are as follows:
L=[Δ X, Δ Y, Δ Z, Δ Vx, Δ Vy, Δ Vz]T
Wherein, Δ X is inertial navigation system along course position error, and Δ Y is that the vertical course position of inertial navigation system misses
Difference, Δ Z are inertial navigation system short transverse location error, and Δ Vx is inertial navigation system along course velocity error, and Δ Vy is
The vertical course velocity error of inertial navigation system, Δ Vz are inertial navigation system short transverse velocity error.
After obtaining position error vector sum observing matrix, it can be reversed and calculate inertial navigation error parameter to be estimated.
Preferably, inertial navigation error, the auto-correlation of observation noise vector n can also be assessed by observation noise vector n
Matrix CnIt indicates are as follows:
E(nnT)=Cn
Autocorrelation matrix C can be passed throughnAssess inertial navigation error.
Inertial navigation method for estimating error provided in this embodiment is improved by carrying out subgraph imaging to echo-signal
The operation efficiency of inertial navigation estimation error, and position error vector by calculating separately each ground control point, construction
Observing matrix can obtain high-precision inertial navigation error vector, be suitable for processing in real time.
Optionally, in some embodiments, it before the first geographical coordinate for obtaining m ground control point respectively, also wraps
It includes:
M ground control point, preset condition are chosen according to preset condition are as follows:
Wherein, xiIt is i-th of ground control point in the coordinate on aircraft motion direction, yiFor i-th of ground control point
Perpendicular to the coordinate on aircraft motion direction, HiFor the height of i-th of ground control point, xjIt is j-th of ground control point on edge
Coordinate on aircraft motion direction, yjIt is j-th of ground control point perpendicular to the coordinate on aircraft motion direction, HjFor jth
The height of a ground control point, K are the number of ground control point, and K >=3.
Optionally, in some embodiments, it is imaged according to m ground control point and echo-signal, obtains m son
Image specifically includes:
Centered on each ground control point, m subgraph imaging grid is established；
Each subgraph imaging grid is imaged respectively according to default imaging algorithm and echo-signal, obtains m son
Image.
Optionally, in some embodiments, presetting imaging algorithm is back-projection algorithm.
As shown in Fig. 2, giving a kind of illustrative imaging geometry model schematic, X-axis is in imaging geometry coordinate system
It is along directional velocityDirection, Y-axis are perpendicular to directional velocityDirection, Z axis are directed toward ground and areDirection.Point P be to
Imageable target point, there are relative motion relation, (x with point P for carrier aircraftp,yp,zp) it is that P point is with O point under imaging geometry coordinate system
Coordinate of the coordinate origin in X, Y, Z axis.Back-projection algorithm is a kind of accurate time-domain imaging method, and image-forming principle can be with table
It is shown as:
Wherein, I (m, n) is the imaging results that the pixel that coordinate in grid is (m, n) is imaged, and S (k) is k-th of pulse
Signal after pulse pressure, K are the number of effective impulse, and R (k, m, n) is k-th of pulse time antenna phase center to imaging
Coordinate is the distance of the pixel of (m, n) in grid, and λ is wavelength.
Optionally, in some embodiments, the size of each subgraph imaging grid are as follows:
ΔU≥2δumax
Wherein, Δ U is the size that grid is imaged in subgraph, δ umaxMost for image position error under default precision conditions
Big value.
It should be noted that default precision conditions can be arranged according to actual needs, for example, can be with existing inertial navigation precision
Condition.
When the size of each subgraph imaging grid meets above-mentioned condition, it can be ensured that the imaging knot of ground control point
Fruit is in subgraph grid.
Optionally, in some embodiments, inertial navigation error vector is estimated according to the following formula:
Wherein,For the estimated value of inertial navigation error vector, G is position error vector, and H is observing matrix.
Optionally, in some embodiments, position error vector G is indicated are as follows:
G=[Δ x1,Δy1,...,Δxm,Δym]T
Wherein, Δ x1With Δ y1The 1st ground control point is respectively indicated along the position error in course and vertical course, with this
Analogize, m indicates the sum of ground control point.
Optionally, in some embodiments, observing matrix H is indicated are as follows:
Wherein, V is carrier aircraft along course movement velocity, x1Indicate the 1st coordinate of the ground control point along course direction, y1Table
Show the coordinate in the vertical course direction of the 1st ground control point, z1The coordinate of the 1st ground control point short transverse is indicated, with this
Analogize, m indicates the sum of ground control point.
Optionally, in some embodiments, inertial navigation error vector includes: the vertical boat along course position error delta X
To location error Δ Y, short transverse location error Δ Z, along course velocity error Δ Vx, vertical course velocity error Δ Vy is high
Spend direction velocity error Δ Vz.
Below with reference to some specific examples, it is further described.
Simulating, verifying is carried out to evaluation method proposed by the present invention below, the present invention uses BP algorithm, i.e. rear orientation projection calculates
Method, comparative experiments use traditional R-D model, are illustrated below by emulation data and measured data.
It can be emulated by softwares such as matlab, experiment parameter is as shown in table 1.
1 experiment parameter table of table
Example one: vector to be estimated is set as P1=[3,5,8,0.6,0.5, -0.5]T, first group of ground control point
(Ground Control Point, GCP) coordinate is as shown in table 2.
2 ground control point coordinate of table
As shown in figure 3, (a) of Fig. 3-(f) be respectively under traditional R-D model estimation technique and the BP imaging model estimation technique,
Estimation mean square error of 6 parameters to be estimated tested by 10000 Monte-Carlo under two kinds of estimation methods
(Cramer-Rao Bound, CRB) comparing result, 6 parameters to be estimated are respectively as follows: inertial navigation system along course position error
Δ X, the vertical course position error delta Y of inertial navigation system, inertial navigation system short transverse location error Δ Z, inertial navigation
System is along course velocity error Δ Vx, the vertical course velocity error Δ Vy of inertial navigation system, inertial navigation system short transverse
Velocity error Δ Vz.Wherein, "+" represents the BP imaging model estimation technique, and " o " represents the R-D model estimation technique.
As can be seen that testing to obtain comparing result according to 10000 Monte-Carlo, wherein including inertial navigation position
Error and inertial navigation velocity error are respectively in the mean square error of X-direction, Y-direction and Z-direction estimation and pair of CRB theoretical value
Answer result.Fig. 3 result explanation, under the conditions of identical observation noise mean square error, the ins error estimation method of BP imaging model
The available smaller estimation mean square error compared with traditional R-D model ins error estimation method.
Example two: with the method for the present invention to measured data processing, measured data comes from X-band airborne synthetic aperture radar
(Synthetic Aperture Radar, SAR), experiment parameter is identical as the simulation parameter of table 1.
The scene chosen is tested as shown in figure 4, the corresponding optical imagery of the experiment scene in the scene as shown in figure 5, contain
There are some strong scattering regions with obvious characteristic.One group of preset error vector P is added in benchmark inertial guidance data2=
[10,20,10,0.1,0.2,-0.5]T, evaluated error of the more of the invention and two kinds of algorithm for estimating of R-D model to ins error
As shown in table 3.
From table 3 it can be seen that evaluation method of the invention be based on existing R-D model inertial navigation method for parameter estimation phase
Than available lesser inertial navigation location error and inertial navigation velocity error.
The estimated result comparison that each exercise parameter of table 3 passes through two kinds of algorithm for estimating
Example three: just the present invention and existing R-D model inertial navigation method for parameter estimation operation efficiency compare below,
In for the data block size of comparison be 65536 × 4096 (orientation × distance to) points, the imaging of R-D model is divided into 32 sons
Aperture processing, each sub-aperture have 1/2 overlapping region.Subgraph imaging sizing grid of the present invention is 256 × 256 points, grid list
Member is 0.5m.As shown in fig. 6, changing schematic diagram for illustrative ground control point quantity and operation time, it is seen that the present invention with
Existing R-D model compares operation efficiency with higher.
It is appreciated that in some embodiments, may include such as implementation optional some or all of in the various embodiments described above
Mode.
In other embodiments of the invention, a kind of storage medium is also provided, instruction is stored in the storage medium, when
When computer reads the instruction, computer is made to execute the inertial navigation error estimation side as described in any one of above-described embodiment
Method.
Reader should be understood that in the description of this specification reference term " one embodiment ", " is shown " some embodiments "
The description of example ", " specific example " or " some examples " etc. means specific features described in conjunction with this embodiment or example, knot
Structure, material or feature are included at least one embodiment or example of the invention.In the present specification, to above-mentioned term
Schematic representation need not be directed to identical embodiment or example.Moreover, description specific features, structure, material or
Feature may be combined in any suitable manner in any one or more of the embodiments or examples.In addition, in not conflicting situation
Under, those skilled in the art by different embodiments or examples described in this specification and different embodiment or can show
The feature of example is combined.
It is apparent to those skilled in the art that for convenience of description and succinctly, the dress of foregoing description
The specific work process with unit is set, can refer to corresponding processes in the foregoing method embodiment, details are not described herein.
In several embodiments provided herein, it should be understood that disclosed device and method can pass through
Other modes are realized.For example, the apparatus embodiments described above are merely exemplary, for example, the division of unit, only
Only a kind of logical function partition, there may be another division manner in actual implementation, such as multiple units or components can be tied
Another system is closed or is desirably integrated into, or some features can be ignored or not executed.
Unit may or may not be physically separated as illustrated by the separation member, show as unit
Component may or may not be physical unit, it can it is in one place, or may be distributed over multiple nets
On network unit.Some or all of unit therein can be selected to realize the embodiment of the present invention according to the actual needs
Purpose.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, is also possible to two or more units and is integrated in one unit.It is above-mentioned integrated
Unit both can take the form of hardware realization, can also realize in the form of software functional units.
If integrated unit is realized in the form of SFU software functional unit and when sold or used as an independent product,
It can store in a computer readable storage medium.Based on this understanding, technical solution of the present invention substantially or
Person says that all or part of the part that contributes to existing technology or the technical solution can be in the form of software products
It embodies, which is stored in a storage medium, including some instructions are used so that a computer
Equipment (can be personal computer, server or the network equipment etc.) execute each embodiment method of the present invention whole or
Part steps.And storage medium above-mentioned include: USB flash disk, mobile hard disk, read-only memory (ROM, Remd-OmlyMemory),
Random access memory (RMM, RmmdomMccessMemory), magnetic or disk etc. be various to can store program code
Medium.
More than, only a specific embodiment of the invention, but scope of protection of the present invention is not limited thereto, and it is any ripe
It knows those skilled in the art in the technical scope disclosed by the present invention, various equivalent modifications can be readily occurred in or replaces
It changes, these modifications or substitutions should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention Ying Yiquan
Subject to the protection scope that benefit requires.
Claims (10)
1. a kind of inertial navigation method for estimating error of airborne synthetic aperture radar characterized by comprising
The first geographical coordinate of m ground control point, m >=3 are obtained respectively；
Obtain the echo-signal that airborne synthetic aperture radar detects target area；
It is imaged according to the m ground control points and the echo-signal, obtains m subgraph；
The second geographical coordinate of ground control point described in each subgraph is extracted respectively, it is geographical according to described first respectively
Coordinate and second geographical coordinate obtain the position error vector of each ground control point；
Observing matrix is constructed according to the first geographical coordinate of all ground control points；
It estimates to obtain the inertia of the airborne synthetic aperture radar according to observing matrix described in all position error vector sums
Navigation error vector.
2. inertial navigation method for estimating error according to claim 1, which is characterized in that obtain m ground control respectively
Before first geographical coordinate of point, further includes:
M ground control point, the preset condition are chosen according to preset condition are as follows:
Wherein, xiIt is i-th of ground control point in the coordinate on aircraft motion direction, yiIt is i-th of ground control point vertical
Coordinate on aircraft motion direction, HiFor the height of i-th of ground control point, xjIt is transported for j-th of ground control point along carrier aircraft
Coordinate on dynamic direction, yjIt is j-th of ground control point perpendicular to the coordinate on aircraft motion direction, HjIt is controlled for j-th of ground
The height of point is made, K is the number of ground control point, and K >=3.
3. inertial navigation method for estimating error according to claim 1, which is characterized in that controlled according to the m ground
Point and the echo-signal are imaged, and are obtained m subgraph, are specifically included:
Centered on each ground control point, m subgraph imaging grid is established；
Each subgraph imaging grid is imaged respectively according to default imaging algorithm and the echo-signal, obtains m
A subgraph.
4. inertial navigation method for estimating error according to claim 3, which is characterized in that after the default imaging algorithm is
To projection algorithm.
5. inertial navigation method for estimating error according to claim 3, which is characterized in that net is imaged in each subgraph
The size of lattice are as follows:
ΔU≥2δumax
Wherein, Δ U is the size that grid is imaged in subgraph, δ umaxFor the maximum value for presetting image position error under precision conditions.
6. inertial navigation method for estimating error according to any one of claim 1 to 5, which is characterized in that according to following
Formula estimates the inertial navigation error vector:
Wherein,For the estimated value of inertial navigation error vector, G is position error vector, and H is observing matrix.
7. inertial navigation method for estimating error according to claim 6, which is characterized in that the position error vector G table
It is shown as:
G=[Δ x1,Δy1,...,Δxm,Δym]T
Wherein, Δ x1With Δ y1The 1st ground control point is respectively indicated along the position error in course and vertical course, and so on,
The sum of m expression ground control point.
8. inertial navigation method for estimating error according to claim 6, which is characterized in that the observing matrix H is indicated are as follows:
Wherein, V is carrier aircraft along course movement velocity, x1Indicate the 1st coordinate of the ground control point along course direction, y1Indicate the 1st
The coordinate in the vertical course direction of a ground control point, z1Indicate the coordinate of the 1st ground control point short transverse, and so on, m
Indicate the sum of ground control point.
9. inertial navigation method for estimating error according to claim 6, which is characterized in that the inertial navigation error vector
It include: along course position error delta X, vertical course position error delta Y, short transverse location error Δ Z, along course velocity error
Δ Vx, vertical course velocity error Δ Vy, short transverse velocity error Δ Vz.
10. a kind of storage medium, which is characterized in that instruction is stored in the storage medium, when computer reads described instruction
When, so that the computer is executed inertial navigation method for estimating error as claimed in any one of claims 1-9 wherein.
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