CN110285805A - A kind of adaptive-interpolation/division processing method of data void holes - Google Patents

A kind of adaptive-interpolation/division processing method of data void holes Download PDF

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CN110285805A
CN110285805A CN201910573267.2A CN201910573267A CN110285805A CN 110285805 A CN110285805 A CN 110285805A CN 201910573267 A CN201910573267 A CN 201910573267A CN 110285805 A CN110285805 A CN 110285805A
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rem
data
interpolation
error rate
void holes
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王可东
王涵
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Beihang University
Beijing University of Aeronautics and Astronautics
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Beijing University of Aeronautics and Astronautics
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/005—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C5/00—Measuring height; Measuring distances transverse to line of sight; Levelling between separated points; Surveyors' levels
    • G01C5/005—Measuring height; Measuring distances transverse to line of sight; Levelling between separated points; Surveyors' levels altimeters for aircraft
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/05—Geographic models

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Abstract

The present invention provides a kind of data void holes adaptive-interpolation/splitting scheme, this method can be used for the three-dimensional elevation matching of the REM containing data void holes, belong to Terrain-aided Navigation field.Since data void holes are inevitable in actual match, the invention proposes a kind of effective solution schemes.The invention first classifies to DEM including the use of reference map error rate, extracts the ROI in DEM；Then the interpolation error between REM and ROI is calculated using interpolation error rate, is classified according to interpolation error to data void holes size；Finally REM is handled using adaptive-interpolation/segmentation strategy, data void holes are on the matched influence of three-dimensional elevation in reduction actual match.

Description

A kind of adaptive-interpolation/division processing method of data void holes
Technical field
The present invention provides a kind of data void holes adaptive-interpolation/division processing method, this method can be used for containing data The three-dimensional elevation matching of the real-time elevation map (Real-time Elevation Map, REM) in cavity, belongs to Terrain-aided Navigation Field.
Background technique
Entirely autonomous Models in Terrain Aided Navigation can be widely applied to complex electromagnetic environment, deep space exploration and the neck such as underwater Domain plays satellite navigation or other irreplaceable unique effects of navigation in national economy and national defense construction.With traditional list Point is compared with one-dimensional sequence matching, since sampled point increases considerably in the three_dimensional topograph model based on three-dimensional elevation sampling, greatly Error hiding probability caused by landform similitude is reduced greatly；With the picture of reference map in two-dimentional scene matching aided navigation and the real-time figure of sampling Plain value is that gray value is different, and in three_dimensional topograph model is landform altitude, hypsography marking area matching performance more It is good, so, three-dimensional elevation matching has unique advantage and wide application prospect in terms of high-precision independent navigation.
The basic functional principle of dimensional topography assisting navigation is as shown in Figure 1, first digitize the landform of matching area, structure The benchmark graph data library based on digital elevation model (Digital Elevation Model, DEM) is built, navigation is stored in and calculates In machine；When carrier passes through digitized matching terrain region, using where three-dimensional elevation measurement sensor measurement carrier Landform REM at position；Then, as shown in Fig. 2, with inertial navigation system (Inertial Navigation System, INS) Current location (i, j) centered on, according to INS longitude and latitude direction position error estimate the larger value σ, by 3 σ standard Then, determine that region to be matched, region to be matched include I × J DEM in total in benchmark graph data library, centre coordinate is (i, j) DEM be denoted as DEM(i,j)；Finally, in region to be matched, the DEM reference map for being included by REM and region to be matched is carried out With calculating, matched position is obtained, and the matching position is fed back into INS, corrects the accumulated error of INS.
Common three-dimensional elevation measurement sensor includes interference synthetic aperture radar (Interferometric Synthetic Aperture Radar, InSAR), laser radar (Light Detection and Ranging, LiDAR), Stereo vision camera, ultrasonic range finder and infrared ambulator etc..But these three-dimensional elevation measurement sensors are obtained in real time When taking REM, data void holes are easy to produce, have seriously affected the matching performance and availability of Models in Terrain Aided Navigation.The present invention The producing cause of data void holes is introduced by taking InSAR as an example.
InSAR measurement is the dimensional topography measurement of higher degree technology to grow up in the recent period, is synthetic aperture radar technique The application of (Synthetic Aperture Radar, SAR) extends and extension.InSAR measuring technique utilizes the two of areal Width SAR image obtains dimensional topography elevation image by the processing such as interference and phase unwrapping as basic handling data. InSAR measurement can the work of round-the-clock, round-the-clock, mapping coverage is big, and data-handling efficiency is high.
It is folded to cover and shade due to the geometrical relationship between imaging and ground scene however, as shown in figure 3, in SAR image It is more generally existing phenomenon, especially in the region of the landform altitudes big rise and fall such as mountain area or city.It is folded to cover and shadow region Domain corresponded on phase diagram can not the region that twines of solution, lead to occur shortage of data in REM, data void holes generated, such as Fig. 4 institute Show, wherein the sum of REM data normal point is P, and the number of data void holes is M, and the shortage of data number in than the m-th data cavity is Nm。
In mapping, the shadow of data void holes is eliminated using the complementarity between several figures using multiangular measurement It rings.But since the carrier of application Terrain-aided Navigation is only disposably by target area, multiangular measurement can not be carried out, And Terrain-aided Navigation is in the area navigation better performances of landform altitude big rise and fall, therefore, in the landform measured based on InSAR Data void holes are easy to produce in assisting navigation.In existing correlative study, the feature for having paid close attention to three-dimensional elevation map is mentioned The problems such as taking method, quick computational algorithm and matching algorithm not yet grinds data void holes problem present in three-dimensional elevation measurement Study carefully.Therefore, a kind of data void holes adaptive-interpolation/division processing method is studied, to reduce data void holes to three-dimensional elevation landform The influence of matching performance has important application value.
Summary of the invention
The technology of the present invention solves the problems, such as: interpolation/segmentation strategy is used, using reference map error rate and interpolation error rate, Classify to data void holes, constructs adaptive-interpolation/dividing method of data void holes, improve the performance of Terrain-aided Navigation.
Technical key point of the present invention:
The precision of REM is mainly determined by the Acquisition Error of initial data and elevation interpolation error, wherein data acquisition misses Poor includes mainly three-dimensional elevation measurement sensor error, installation error and data processing error etc., and elevation interpolation error is interpolation Deviation between point and actual measurement elevation.The present invention respectively indicates these two types of miss using reference map error rate and interpolation error rate The size of difference provides the foundation for adaptive-interpolation/dividing method of data void holes.
1. reference map error rate
Reference map error rateIt is defined as follows:
Wherein:Indicate REM and DEM(i,j)Reference map error rate between reference map, data are normally total in REM Number is P；fREM(p) the REM height value normally located for p-th of data；fDEM(p) p-th of data corresponding with REM are normally located DEM height value.
Region to be matched is traversed, traversal mode is as shown in figure 5, calculate the reference map error rate of all areas, given threshold K1, when reference map error rateWhen, it is determined as area-of-interest (Region of Interest, ROI)；WhenWhen, then it is determined as region of loseing interest in；Threshold k1Selection depend on matching algorithm demand, common threshold value has 0.4,0.5 and 0.6 etc..
2. interpolation error rate
If the sum of the data void holes of REM is M, the shortage of data number in than the m-th data cavity is Nm；Share Q region It is judged as ROI, centre coordinate is (iq,jq) ROI be denoted asREM than the m-th data cavity withBetween sky Hole interpolation error rateIt is defined as follows:
Wherein:For the height value of the nth data missing in the than the m-th data cavity of REM after interpolation processing；ForWith the nth data deletion sites in the than the m-th data cavity of REM relative to height value.
REM withBetween interpolation error rateIt is defined as follows:
Wherein max expression is maximized.Interpolation error rate ratioROI, it is defined as follows:
Wherein:Indicate REM withBetween interpolation error rate；Min expression is minimized.Given threshold K2, as data void holes region ratioROI≤K2When, it is determined as small hole region；As data void holes region ratioROI> K2When, sentence It is set to macroscopic-void region；Threshold k2Selection depend on this area to the degrees of tolerance of data void holes size, common threshold value has 0.10,0.15 and 0.20 etc..
3. adaptive-interpolation/splitting scheme
For data void holes different size of in REM, using reference map error rate and interpolation error rate to data void holes into Row classification, to different size of data void holes, proposes corresponding processing method, in which: for lesser data void holes, using slotting Value method carries out polishing to the altitude data of missing；For biggish data void holes, cutting process, cutting method such as Fig. 6 institute are taken Show, if the maximum map sheet REM after cutting meets minimum template requirement, continues to match, otherwise, abandon matching, common mould Plate value has 60 × 60,80 × 80,100 × 100 and 120 × 120 etc..
The advantages of the present invention over the prior art are that:
(1) present invention fully considers the data void holes problem that three_dimensional topograph model faces in practical applications, and proposes to solve Certainly scheme improves the performance of Terrain-aided Navigation.
(2) present invention uses the threshold value method of discrimination of reference map error rate and interpolation error rate, calculates easy, reliability Height, and it is easy to Project Realization.
Detailed description of the invention
Fig. 1 is the structural schematic diagram of terrain auxiliary navigation method；
The schematic diagram that Fig. 2 obtains for region to be matched in real-time matching；
Fig. 3 is the schematic diagram of data void holes production principle；
Fig. 4 is the schematic diagram of data void holes occur in REM；
The schematic diagram traversed when figure error rate calculates on the basis of Fig. 5；
Fig. 6 is the schematic diagram of data void holes cutting；
Fig. 7 is data void holes adaptive-interpolation/splitting scheme flow chart.
Specific embodiment
For data void holes problem present in the matching of dimensional topography elevation, the invention proposes a kind of data void holes are adaptive Answer interpolation/dividing method.To keep present invention implementation purposes, technical schemes and advantages clearer, below in conjunction with attached drawing to this The technical solution of invention is clearly and completely described:
In data void holes adaptive-interpolation/dividing method proposed by the present invention, by data void holes be divided into small data cavity with Big data cavity carries out Completing Missing Values processing using bilinear interpolation to small data cavity；Big data cavity is divided Processing is cut, if remaining area is not less than minimum template size, continues to match, otherwise abandons matching.Process such as Fig. 7 is embodied It is shown, it can be described as follows:
(A) REM is obtained by three-dimensional elevation measurement sensor；
(B) centered on the current current location INS (i, j), in benchmark topographic database determine a window, as to Matching area；
(C) data void holes detection is carried out to REM and is transferred to step (D) if REM contains data void holes；If REM no data Cavity is then transferred to step (G)；
(D) REM and DEM is calculated(i,j)Between reference map error rateWhenWhen, then it is determined as ROI； WhenWhen, then it is determined as region of loseing interest in, stores all ROI location informations；ROI region if it exists is then transferred to Step (E), on the contrary it is transferred to step (H)；
(E) REM is handled using interpolation method, calculates the interpolation error rate ratio between REM and ROIROI, when ratioROI≤K2When, it is judged as small hole region, is transferred to step (G)；Work as ratioROI> K2When, it is determined as macroscopic-void region, turns Enter step (F)；
(F) adaptivenon-uniform sampling processing is carried out to REM, if the maximum map sheet REM after dividing processing, which meets, matches minimum template It is required that being then transferred to step (D)；Conversely, being then transferred to step (H)；
(G) it is matched using three-dimensional elevation matching algorithm, the inertial navigation position is corrected according to obtained matching position, It is transferred to step (I)；
(H) this matching is abandoned.
(I) new REM is read, aforesaid operations are repeated, until matching terminates.
Above embodiments are provided just for the sake of the description purpose of the present invention, and are not intended to limit the scope of the invention.This The range of invention is defined by the following claims, and is not departed from spirit and principles of the present invention and the various equivalent replacements made and is repaired Change, should all cover within the scope of the present invention.

Claims (10)

1. the present invention proposes a kind of adaptive-interpolation/division processing method of data void holes, this method can be used for containing data sky The three-dimensional elevation of the REM in hole matches, characterized by comprising:
A REM) is obtained by three-dimensional elevation measurement sensor；
B) centered on the current location (i, j) of INS, in reference map database determine a search window, as to With region, region to be matched includes I × J DEM in total, and centre coordinate is that the DEM of (i, j) is denoted as DEM(i,j)；
C data void holes detection) is carried out to REM and is transferred to step D if REM contains data void holes)；Otherwise, it is transferred to step G)；
D REM and DEM) is calculated(i,j)Between reference map error rateWhenWhen, then it is determined as ROI；WhenWhen, then it is determined as region of loseing interest in.Region to be matched is traversed, all reference map error rates are calculated, storage is all ROI location information.ROI region if it exists is then transferred to step E)；Otherwise, it is transferred to step H)；
E) REM is handled using interpolation method, calculates the interpolation error rate ratio between REM and all ROIROI, work as ratioROI ≤K2When, it is judged as small hole region, is transferred to step G)；Work as ratioROI> K2When, it is determined as macroscopic-void region, is transferred to step F)；
F adaptivenon-uniform sampling processing) is carried out to REM, if the maximum map sheet REM after dividing processing, which meets, matches minimum template requirement, Then it is transferred to step D)；Otherwise, it is transferred to step H)；
G it) is matched using three-dimensional elevation matching algorithm, the inertial navigation position is corrected according to obtained matching position；
H this matching) is abandoned.
2. data void holes adaptive-interpolation/division processing method according to claim 1, it is characterised in that:
Step A) used in measurement of higher degree sensor further comprise InSAR, LiDAR, stereo vision camera, ultrasonic distance measurement Instrument, multibeam sonar and infrared ambulator etc..
3. data void holes adaptive-interpolation/division processing method according to claim 1, it is characterised in that:
Step B) further comprise:
Centered on the current location (i, j) of INS, according to INS longitude and latitude direction position error estimate the larger value σ determines region to be matched by 3 σ criterion in reference map database.
4. data void holes adaptive-interpolation/division processing method according to claim 1, it is characterised in that:
Step C) further comprise:
The presence or absence of data void holes in REM is judged using connected domain detection, and data void holes region is marked, wherein REM number Sum according to normal point is P, and the number of data void holes is M, and the shortage of data number in than the m-th data cavity is Nm。
5. data void holes adaptive-interpolation/division processing method according to claim 1, it is characterised in that:
Step D) further comprise:
Reference map error rateIt is defined as follows:
Wherein:Indicate REM and DEM(i,j)Between reference map error rate, the normal sum of data is P in REM；fREM (p) the REM height value normally located for p-th of data；fDEM(p) DEM normally located for p-th of data corresponding with REM(i,j)It is high Journey value.
6. data void holes adaptive-interpolation/division processing method according to claim 1, it is characterised in that:
Step E) interpolation method further comprises that linear interpolation method, bilinear interpolation, Kriging regression method, nearest neighbor point are inserted Value method, Natural neighbors interpolation method, minimum-curvature method, image factoring, radial basis function method and inverse distance multiply method etc..
7. data void holes adaptive-interpolation/division processing method according to claim 1, it is characterised in that:
Step E) the interpolation error rate further comprises:
Using reference map error rate, if shared Q region is judged as ROI, centre coordinate is (iq,jq) ROI be denoted asInterpolation error rate ratioROIIt is defined as follows:
Wherein:Indicate REM withBetween interpolation error rate；Min expression is minimized.
8. data void holes adaptive-interpolation/division processing method according to claim 1, it is characterised in that:
Step F) further comprise:
Adaptivenon-uniform sampling processing utilizes interpolation error rate as claimed in claim 7, and REM is cut in label maximum data cavity Cut processing.Whether it is not less than minimum stencil value according to the REM map sheet after cutting, judges whether to match, common minimum modulus Plate value has 60 × 60,80 × 80,100 × 100,120 × 120 etc..
9. interpolation error rate according to claim 7, it is characterised in that:
The REM withBetween interpolation error rate further comprise:
According to the number of REM data void holes known to claim 4 be M, REM withBetween interpolation error rateIt is fixed Justice is as follows:
Wherein:Indicate REM than the m-th data cavity withBetween empty interpolation error rate；Max expression takes maximum Value.
10. interpolation error rate according to claim 9, it is characterised in that:
The cavity interpolation error rate further comprises:
It is N according to the shortage of data number in the than the m-th data cavity of REM known to claim 4m, REM than the m-th data cavity withBetween empty interpolation error rateIt is defined as follows:
Wherein:For the height value of the nth data missing in the than the m-th data cavity of REM after interpolation processing；ForThe height value of the nth data deletion sites in the than the m-th data cavity relative to REM.
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CN113936316B (en) * 2021-10-14 2022-03-25 北京的卢深视科技有限公司 DOE (DOE-out-of-state) detection method, electronic device and computer-readable storage medium
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CN115063460B (en) * 2021-12-24 2024-06-25 山东建筑大学 High-precision self-adaptive homonymous pixel interpolation and optimization method

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Application publication date: 20190927