CN103426177A - Moon subsurface position detection method based on moon detection radar - Google Patents

Abstract

The invention discloses a moon subsurface position detection method based on moon detection radar. The method includes the following steps of firstly, conducting median filter on data of the moon detection radar and then conducting hilbert transform processing on the data; secondly, processing the data, processed in the first step, of the moon detection radar through the Canny algorithm to extract edge endpoints; thirdly, wiping isolated edge points out of the binary image data processed in the second step, then, enabling the edge endpoints to be connected with one another through the Bresemham algorithm, and finally wiping off the edges with the lengths smaller than a threshold value and outputting the surface position result. According to the method, the moon subsurface position information can be obtained by processing data collected by the moon detection radar through the edge detection method and the edge connection method.

Description

A kind of moon based on the moon sight radar time top layer layer position detecting method

Technical field

The invention belongs to moon sight radar imagery technical field, relate to particularly a kind of moon based on the moon sight radar time top layer layer position detecting method.

Background technology

The moon sight radar is a kind of time domain detection radar worked in without carrier frequency millimicrosecond pulse state, adopts the bistatic antenna.Its principle of work is: the moon sight radar transmitter produce ultra broadband without the carrier frequency millimicrosecond pulse, through emitting antenna to radiation/coupling super-broadband electromagnetic impulse signal under lunar surface, signal is in the communication process of lunar soil and lunar crust rock medium, if run into the targets such as uneven layer, different medium interface, lava tube, erratic boulder, by the reflection of the signal that generates electromagnetic waves and scattering.After the moon sight radar receiving antenna receives this reflection and scattered signal, after amplifying, sample, receiver obtains corresponding detection data, by detection data is analyzed, processing and imaging, obtain making an inspection tour the information such as the distribution of lunar soil thickness in device walking zone and distribution, erratic boulder and lava tube and lunar crust time top layer rock geologic structure.

The moon sight radar data has reflected the resistance difference of the moon time surface materials, it is the comprehensive embodiment of specific inductive capacity, conductivity and magnetic permeability difference, also due to the impact of medium heterogeneity, Multi reflection, Ambient, diffraction etc., inevitably there are multi-solution and complicacy in addition.Because the moon sight radar is surveyed for menology first, lack at present the corresponding position detecting method of layer targetedly.Effectively the tracing of horizons method can improve the Detection and identification ability of system, obtains the information of the moon time top layer inner structure.

Summary of the invention

The purpose of this invention is to provide a kind of based on the moon sight radar the moon time top layer layer position detecting method, to obtain the moon time top layer inner structure hierarchical information.

For achieving the above object, the moon sight radar layer position detecting method based on Image Edge-Detection provided by the invention comprises step: step 1, and the moon sight radar data is carried out to medium filtering, then carry out the Hilbert transform processing; Step 2, adopt the Canny algorithm to be processed to the moon sight radar data after step 1 is processed, and extracts the edge end points; Step 3, remove isolated marginal point to the binary image data after step 2 is processed, and then uses Bresemham algorithm fillet acies point, finally removes the edge that length is less than threshold value, output layer position result.

Preferably, described medium filtering is to the sequence of the image pixel gray-scale value in a moving window, replaces the filtering of window center grey scale pixel value by its intermediate value.

Preferably, described Hilbert transform, for adopting Hilbert transform to extract the envelope of radar echo signal, reduces the edge detected.

Preferably, described Canny algorithm is, at first adopts the first order derivative of two-dimensional Gaussian function to carry out smoothly image, then by gaussian kernel gradient vector and image convolution, then carries out non-maximum value and suppresses the two-value marginal end dot image be enhanced.

Preferably, described two-dimensional Gaussian function is

X wherein, y is respectively the image pixel horizontal ordinate, ordinate, σ is the function width parameter.

Preferably, described gaussian kernel gradient vector is $\▿G=\left[\begin{array}{c}\∂G/\∂x\\ \∂G/\∂y\end{array}\right].$

Preferably, described Bresemham algorithm comprises, removes isolated edge end points, connects the neighboring edge end points, deletes the threshold values outward flange, output layer position information.

The present invention adopts rim detection and edge method of attachment, processes moon sight radar image data and can obtain the moon time layer position, top layer information.

The accompanying drawing explanation

Fig. 1 is the moon time top layer layer position detecting method process flow diagram that the present invention is based on the moon sight radar;

Fig. 2 is the Bresemham connection diagram;

Fig. 3 is the raw data gray-scale map;

Fig. 4 is instantaneous peak value data gray-scale map after Hilbert transform;

Fig. 5 is the two-value data Output rusults figure after maximum value suppresses;

Fig. 6 is that two-value data is deleted minor face edge aftertreatment figure as a result;

Fig. 7 carries out edge to connect rear Output rusults figure;

Fig. 8 is that Output rusults is superimposed to design sketch after former figure.

Embodiment

For making the purpose, technical solutions and advantages of the present invention clearer, below in conjunction with specific embodiment, and, with reference to accompanying drawing, the present invention is described in more detail.

The present invention proposes a kind of moon for the moon sight radar time top layer layer position detecting method, realize that the ultimate principle of the method is: the moon sight radar data is slided to the window medium filtering, adopt Hilbert transform to extract the image envelope; Use the first order derivative of two-dimensional Gaussian function to carry out smoothing processing to the envelope image obtained; The image that gradient vector and original image convolution are enhanced; Carry out non-maximum value inhibition, obtain bianry image; The binary image data obtained is removed to isolated marginal point; Then use Bresemham method fillet acies point; Finally remove the edge that length is less than threshold value, output layer position result.The present invention adopts rim detection and edge method of attachment, processes moon sight radar image data and can obtain the moon time layer position, top layer information.

Fig. 1 is the moon time top layer layer position detecting method process flow diagram that the present invention is based on the moon sight radar.With reference to Fig. 1, the method comprises following steps:

Step 1, the data pre-service.The detection data that the moon sight radar obtains as shown in Figure 3, totally 512 track datas, 512 points of every track data, adopt the gray scale display mode.

In this step, at first the moon sight radar data is carried out to medium filtering, then carry out Hilbert Hilbert conversion process.Wherein, medium filtering is to the sequence of the image pixel gray-scale value in a moving window, replaces the filtering method of window center grey scale pixel value by its intermediate value, can eliminate noise.Then carry out Hilbert transform, obtain instantaneous amplitude (envelope) and instantaneous phase, be stored as respectively image array, be illustrated in figure 4 instantaneous amplitude.Hilbert is transformed to the envelope that adopts the Hilbert conversion to extract echoed signal, reduces the edge detected.

Step 2, rim detection.

In this step, to the moon sight radar data after step 1 is processed, adopt the Canny method to be processed, extract the edge end points.Wherein the Canny method is: the first order derivative that at first adopts two-dimensional Gaussian function is carried out smoothing processing to the envelope image obtained, and establishes two-dimensional Gaussian function and is:

$G(x,y)=\frac{1}{2{\mathrm{\π\σ}}^2}\exp [-\frac{x^2+y^2}{2{\mathrm{\σ}}^2}]---\left(1\right)$

X, y is respectively image pixel horizontal ordinate and ordinate, and σ is the function width parameter, and its gradient vector is:

$\▿G=\left[\begin{array}{c}\∂G/\∂x\\ \∂G/\∂y\end{array}\right]---\left(2\right)$

The image that gradient vector and image F (x, y) convolution after step 1 is processed are enhanced.Obtain output image I (x, y)

$E_x(x,y)=\frac{\∂G}{\∂x}\⊗F(x,y)---\left(3\right)$

$I(x,y)=\frac{\∂G}{\∂y}\⊗E_x(x,y)---\left(4\right)$

Element value in the output image gradient magnitude matrix obtained is larger, and in the key diagram picture, the Grad of this point is larger, but this can not illustrate that this point is exactly edge.For accurate edge, location, ridge band that must refinement gradient magnitude image, only retain the point of localized variation maximum, and non-maximum value suppresses.At first judge in 3 * 3 zones whether the current pixel point gray-scale value is maximum in its 8 value neighborhood take centered by current pixel point.Both by finding out the gradient line direction of current pixel point, relatively along the adjacent pixel intersection point 1 of this this gradient line direction and the value of pixel intersection point 2.If, through judgement, determine that the current pixel point gray-scale value is less than any in these two points, that just illustrates that this point is not local maximum, and so can get rid of this point is edge.Finally obtain the bianry image that contains marginal information, the some gray-scale value at non-edge is 0, and may its gray scale can be set for the local gray level maximum point at edge is 128, as shown in Figure 5.

Step 3, edge connects.

To the binary image data obtained after step 2 is processed, adopt the dual threshold method to remove isolated marginal point, reduce false amount of edge.Select two threshold values, according to high threshold, obtain an edge image, such image contains false edge seldom, but, because threshold value is higher, the image border of generation may be not closed, in order to address such a problem, adopted another one to hang down threshold value.In the high threshold image, edge is connected into to profile, when arriving the end points of profile, find the point that meets low threshold value in 8 neighborhood points of breakpoint, then collect new edge according to this point, until whole image border closure, the output result as shown in Figure 6.

Then use Bresemham method fillet acies point, Output rusults as shown in Figure 7, is finally removed the edge that length is less than threshold value, and output layer position result is added on raw data, as shown in Figure 8.

In this step, above-mentioned Bresemham method is: as shown in Figure 2, suppose that the coordinate of line segment end points is respectively D ₁(x ₁, y ₁) and D ₂(x ₂, y ₂), and the slope range of line segment is between 0 and 1.After conversion, D1 is expressed as (0,0), and D2 is expressed as (Δ a, Δ b)=(x ₂-x ₁, y ₂-y ₁), now straight-line equation can be expressed as

$y=\frac{\mathrm{\Δb}}{\mathrm{\Δa}}x---\left(5\right)$

Suppose the current some P generated _I-1Coordinate is (a _I-1, b _I-1), R _iCoordinate be (a _I-1+ 1, b _I-1), Q _iCoordinate be (a _I-1+ 1, b _I-1+ 1), the theoretic Accurate Points Si of straight line is apart from the actual pixel R that can select of the next one _iAnd Q _iDistance be respectively r _iAnd q _i:

$r_i=\frac{\mathrm{\Δb}}{\mathrm{\Δa}}(a_{i-1}+1)-b_{i-1}---\left(6\right)$

$q_i=(b_{i-1}+1)-\frac{\mathrm{\Δb}}{\mathrm{\Δa}}(a_{i-1}+1)---\left(7\right)$

By formula (6), formula (7) can obtain

Δa(r _i-q _i)=2(a _i-1Δb-b _i-1Δa)+2Δb-Δa （8）

Order

Initial value

According to Whether be greater than the zero quick selection realized next pixel.If work as

r _i>=q _i, select Q _iPoint is next pixel, next step error factor

For

${\▿}_{i+1}={\▿}_i+2\mathrm{\Δb}-2\mathrm{\Δa}---\left(9\right)$

When

r _i<q _i, select R _iPoint is next pixel, next step error factor

For

${\&dtri;}_{i+1}={\&dtri;}_i+2\mathrm{\&Delta;b}---\left(10\right)$

According to initial value and the iterative formula of error factor, just can draw each point on line segment.Whole algorithm flow schematic diagram as shown in Figure 2.

Above-described specific embodiment; purpose of the present invention, technical scheme and beneficial effect are further described; be understood that; the foregoing is only specific embodiments of the invention; be not limited to the present invention; within the spirit and principles in the present invention all, any modification of making, be equal to replacement, improvement etc., within all should being included in protection scope of the present invention.

Claims (7)

1. time top layer layer position detecting method of the moon based on the moon sight radar data, is characterized in that, comprises the following steps: step 1, and the moon sight radar data is carried out to medium filtering, then carry out the Hilbert transform processing; Step 2, adopt the Canny algorithm to be processed to the moon sight radar data after step 1 is processed, and extracts the edge end points; Step 3, remove isolated marginal point to the binary image data after step 2 is processed, and then uses Bresemham algorithm fillet acies point, finally removes the edge that length is less than threshold value, output layer position result.

2. a kind of moon based on the moon sight radar data according to claim 1 time top layer layer position detecting method, it is characterized in that, described medium filtering is to the sequence of the image pixel gray-scale value in a moving window, replaces the filtering of window center grey scale pixel value by its intermediate value.

3. a kind of moon based on the moon sight radar data according to claim 1 time top layer layer position detecting method, is characterized in that, described Hilbert transform, for adopting Hilbert transform to extract the envelope of radar echo signal, reduces the edge detected.

4. a kind of moon based on the moon sight radar data according to claim 1 time top layer layer position detecting method, it is characterized in that, described Canny algorithm is, at first adopt the first order derivative of two-dimensional Gaussian function to carry out smoothly image, then by gaussian kernel gradient vector and image convolution, then carry out non-maximum value and suppress the two-value marginal end dot image be enhanced.

5. a kind of moon based on the moon sight radar data according to claim 4 time top layer layer position detecting method, is characterized in that, described two-dimensional Gaussian function is X wherein, y is respectively the image pixel horizontal ordinate, ordinate, σ is the function width parameter.

6. a kind of moon based on the moon sight radar data according to claim 4 time top layer layer position detecting method, is characterized in that, described gaussian kernel gradient vector is $\&dtri;G=\left[\begin{array}{c}\&PartialD;G/\&PartialD;x\\ \&PartialD;G/\&PartialD;y\end{array}\right].$

7. a kind of moon based on the moon sight radar data according to claim 1 time top layer layer position detecting method, it is characterized in that, described Bresemham algorithm comprises: remove isolated edge end points, connect the neighboring edge end points, delete the threshold values outward flange, output layer position information.

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