CN112346057A - Two-dimensional interpolation module in image processing process - Google Patents
Two-dimensional interpolation module in image processing process Download PDFInfo
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Abstract
The invention relates to a two-dimensional interpolation module in an image processing process, which comprises a multi-channel data distribution module, an interpolation module and a multi-channel data integration module: the multi-path data distribution module outputs data in a time-sharing manner, and the data are transmitted into the parallel interpolation processing module in a flowing manner; an interpolation module: the system comprises a distance direction interpolation module and a direction interpolation module; respectively calculating distance direction interpolation positions and azimuth direction interpolation positions and interpolating; and the multi-path data integration module integrates the interpolation results output by the distance and azimuth interpolation processing into one path respectively for output. The module has strong real-time performance and obviously improves the image data processing speed.
Description
The technical field is as follows:
the invention can be applied to the field of image processing, and particularly relates to imaging signal processing of a synthetic aperture radar in a bunching mode.
Background
At present, when a Synthetic Aperture Radar (SAR) in a beamforming mode is used for focusing imaging, a Polar Format Algorithm (PFA) is usually used to perform a preliminary processing on received Radar echo data, and then a FAST Fourier Transform (FFT) is performed to implement focusing imaging on a target. However, the actual radar echo data is mapped to the spatial frequency domain and arranged in a polar coordinate format, and cannot meet the requirement that two-dimensional FFT needs orthogonal and uniform sampling in the spatial frequency domain, so that the polar coordinate format data needs to be converted into rectangular format data, that is, distance direction and azimuth direction interpolation needs to be performed first.
The traditional interpolation is single-path serial processing, a large amount of CPU running time is consumed, the real-time performance is poor, and the radar imaging system with extremely high real-time requirement cannot be accepted, so that the interpolation process becomes one of bottlenecks for limiting the radar signal processing speed.
Disclosure of Invention
The invention provides a two-dimensional interpolation module in an image processing process aiming at the technical problem of poor instantaneity in the interpolation process, the module is based on a Field-Programmable Gate Array (FPGA) device, skillfully provides a distance direction and orientation direction parallel interpolation operation structure suitable for large data volume occasions, and accelerates the interpolation speed and saves storage resources through a linear derivation method. The module has strong real-time performance and obviously improves the image data processing speed.
The invention relates to a two-dimensional interpolation module in an image processing process, which is characterized by comprising a multi-channel data distribution module, an interpolation module and a multi-channel data integration module:
the multi-path data distribution module comprises a multi-path distance direction data distribution module and a multi-path direction data distribution module;
the multi-path distance is transmitted to the data distribution module: dividing the preprocessed input data into multiple channels, outputting in a time-sharing manner, and sending the stream into parallel distance interpolation processing modules;
the multi-way azimuth data distribution module: dividing data subjected to distance data interpolation into multiple channels, outputting in a time-sharing manner, and sending running water into parallel azimuth interpolation processing modules;
an interpolation module: the system comprises a distance direction interpolation module and a direction interpolation module; respectively calculating distance direction interpolation positions and azimuth direction interpolation positions and interpolating;
and the multi-path data integration module integrates the interpolation results output by the distance and azimuth interpolation processing into one path respectively for output.
Further, the distance direction interpolation module calculates the distance direction interpolation position by adopting a derivation method.
Further, the distance direction interpolation module is:
interpolation position X is
Will interpolate position XnDecomposed into integer parts MnAnd a fractional part LnThen, then
Outputting interpolated signal Dout expressed as
Dout(n+1)＝[Din(Mn+1)-Din(Mn)]·Ln+Din(Mn)
n is the number of data blocks; din is an input radar echo signal; initial value K of distance direction data before and after interpolationy_in0、Ky_out0And an incremental value Δ Ky_in、ΔKy_outAnd outputs a signal Dout interpolated over a distance.
Further, the azimuth interpolation module calculates the azimuth interpolation position by using a search method.
Further, the azimuth interpolation module is:
will Kx_outThe 4096 data are sequentially summed with K from large to small or from small to largex_inThe nth data K is obtained by comparing the data in (1)x_out(n) at Kx_inA position in the sequence, the position being an integer part of an interpolated positionDivide MnAnd is obtained at Kx_out(n) left side data Kx_in(Mn) And data K on the rightx_in(Mn+1)；
After the interpolation position M and the corresponding data are obtained, the fractional part L of the interpolation position needs to be calculated, and then
Estimating according to the interpolation position M and the data Dout interpolated by the distance direction to obtain an interpolated signal Dout', wherein the expression is
Dout'(n+1)＝[Dout(Mn+1)-Dout(Mn)]·Ln+Dout(Mn)。
Further, the distance distribution channels and the distance interpolation modules have the same number; the number of the azimuth distributing channels is the same as that of the azimuth interpolation modules.
Further, the module operates on an array of field programmable logic gates.
Has the advantages that:
(1) interpolation calculation is realized by selecting a reasonable parallel pipeline structure, the interpolation processing speed is greatly improved, the performance indexes such as the calculation speed of linear interpolation, hardware resource occupation and the like are optimized, and the method can be widely applied to radar imaging processing.
(2) For data uniformly distributed in the coordinate direction, an interpolation position derivation method is used to obtain an interpolation position, all coordinate data in the distance direction and the azimuth direction do not need to be stored, and only derivation is needed according to the initial value and the incremental value, so that the storage resources can be effectively saved, and the efficiency of interpolation calculation is greatly improved. For data which are non-uniformly distributed in the coordinate direction, an interpolation position is obtained by using an interpolation position searching method, the sizes of all data do not need to be compared, only the data before and after the interpolation position need to be found, and the efficiency of interpolation calculation can be improved.
(3) The advantages of FPGA full-parallel pipeline processing, low power consumption, rich triggers and I/O pins and the like are exerted, the rapid operation of linear interpolation is completed, and the performance indexes of the linear interpolation, such as speed, precision, hardware cost and the like, are optimized.
The method has higher processing speed, can solve the problem that software such as a digital signal processor and the like cannot meet the real-time requirement of the radar imaging system, and greatly improves the speed of interpolation operation so as to meet the requirement of the radar imaging system on higher real-time requirement of linear interpolation.
Drawings
FIG. 1 is a schematic flow chart of the present invention
FIG. 2 is a timing diagram of a distance to data distribution module in an embodiment
FIG. 3 is the azimuth data distribution module timing sequence in the embodiment
FIG. 4 is a search process of azimuth interpolation position in the embodiment
FIG. 5 is a timing diagram of the distance data integration module in one embodiment
FIG. 6 is a timing diagram of an orientation data integration module according to an embodiment
DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION
Before two-dimensional interpolation calculation is carried out on radar echo data, distance direction matched filtering and motion compensation on a scene center are carried out on a received two-dimensional echo signal, and a signal before interpolation is obtained, and the preprocessing process is carried out. The preprocessing process is a common means in the prior art, and is based on the assumption of plane wavefront to obtain the distance direction K before interpolationy_inAnd the interpolated distance direction Ky_outInterpolation of the forward bit direction Kx_inAnd the interpolated azimuth direction Kx_outAnd the data is used as input data and sent to an interpolation processing module. The input data comprises data before and after interpolation in two coordinate directions (K)y_in，Ky_out，Kx_in，Kx_out) And radar echo data (Din) that is distance-wise matched filtered and motion compensated to the center of the scene.
Because a large amount of time is consumed for interpolation processing, and the waiting time after data input is too long can cause resource waste, the invention uses a multi-path parallel structure to process data. The system specifically comprises a multi-path data distribution module, an interpolation module and a multi-path data integration module.
One-way and multi-way data distribution module
The multi-path data distribution module comprises a multi-path distance direction data distribution module and a multi-path direction data distribution module.
1. A multi-path distance data distribution module;
dividing the preprocessed input data into channels with the same number as that of the distance interpolation modules, outputting the input data in a time-sharing mode through different channels, and sending running water into the parallel distance interpolation processing modules.
The distance direction and azimuth direction data block sizes selected by the present embodiment are 4096 points.
Because the distance direction position is calculated by adopting a derivation method, the calculation amount is small, the distance direction data distribution module divides the input data into two paths for time-sharing output and sends the two paths to the distance direction interpolation processing module, and a time sequence chart is shown in fig. 2. As can be seen from the figure, the channel 0 and the channel 1 respectively send input data at different times, and a foundation is laid for the interpolation processing of the subsequent two parallel paths of distances.
2. A multi-path azimuth data distribution module;
dividing the data after the distance data interpolation into channels with the same number as the azimuth interpolation module, outputting the data in a time-sharing manner through different channels, and sending the data in a running water manner into parallel azimuth interpolation processing modules.
And determining the azimuth interpolation position by adopting a search method. Compared with the derivation method, the search method has larger calculation amount and needs longer time to calculate, in this embodiment, the azimuth data distribution module divides the input data into five paths to output in a time-sharing manner, and sends the five paths to the azimuth interpolation processing module, and a timing chart is shown in fig. 3. As can be seen from the figure, the channel 0, the channel 1, the channel 2, the channel 3, and the channel 4 respectively transmit input data at different times, which lays a foundation for the subsequent five-way parallel azimuth interpolation processing.
The data volume and the calculation efficiency are different in different embodiments, and the number of paths distributed by the data distribution module can be adjusted to minimize the processing time.
Second, interpolation module
The interpolation module comprises a distance direction interpolation module and a direction interpolation module. Both include calculating the interpolation position and interpolating. Calculating interpolation position requires obtaining different coordinate directions K before and after interpolationin、KoutSize relationship of data, record KoutEach data in the table corresponds to KinThe position of (2) is taken as an interpolation position.
1. The distance direction interpolation module has the functions of calculating the distance interpolation position and interpolating, converting data distributed in a sector space domain into data distributed in a trapezoid shape, and inputting data into a radar echo signal Din and an initial value K of distance direction data before and after interpolationy_in0、Ky_out0And an incremental value Δ Ky_in、ΔKy_outAnd outputs a signal Dout interpolated over a distance.
(1) Deriving distance interpolated position
Two distance coordinate data K before and after distance interpolationy_inAnd Ky_outThe distribution is uniform, the initial value and the increment value are known, all data in two coordinate directions do not need to be stored, and the interpolation position is deduced according to a linear deduction module, so that a large amount of processing time can be saved. The calculation of the interpolated position X can be simplified to
Will interpolate position XnDecomposed into integer parts and fractional parts, then
n is the number of data blocks.
(2) Interpolation
Estimating according to the interpolation position and the input radar echo data Din to obtain an output interpolated signal Dout, wherein the expression is
Dout(n+1)＝[Din(Mn+1)-Din(Mn)]·Ln+Din(Mn)
The distance interpolation module is 2 groups and comprises two parts of distance interpolation position derivation and distance interpolation. The calculation efficiency of the FPGA for carrying out derivation interpolation on 4096 points in data size is 0.5, namely the clock period required by the input data sequence is T, interpolation calculation is started after the sequence input is finished, and interpolation is finished by 2T clock periods. The two distance interpolation processing modules perform ping-pong linear interpolation processing, so that the full flow can be approximately achieved, the calculation efficiency is approximately 1, the processing speed is accelerated, and the processing time is shortened.
2. The azimuth interpolation module has the functions of searching azimuth interpolation positions and interpolating, converting data which are obtained by distance interpolation and distributed in a trapezoidal mode in a space domain into data distributed in a rectangular mode, inputting data into signals subjected to distance interpolation, and outputting signals subjected to distance interpolation and azimuth interpolation. Wherein, the azimuth data Kx_inHas non-uniform coordinate intervals and interpolated azimuth data Kx_outThe coordinate intervals are uniform, so the azimuth interpolation is a non-uniform to uniform resampling process, a derivation method cannot be used, and the magnitude of each direction data to be interpolated needs to be compared with the magnitude of the original direction data to search to obtain the interpolation position. The specific search process is shown in fig. 4, and includes the following steps:
(1) FPGA respectively compares K with Kx_inAnd Kx_outWriting into FIFO memory, and storing Kx_outN data are sequentially summed with Kx_inComparing the data in the sequence from large to small or from small to large (based on the radar data sequence) to obtain Kx_out(n) at Kx_inA position in the sequence which is the integer part M of the interpolated positionnAnd is obtained at Kx_out(n) left side data Kx_in(Mn) And data K on the rightx_in(Mn+1)。
After the interpolation position M and the corresponding data are obtained, the fractional part L of the interpolation position needs to be calculated, and then
(2) Estimating the interpolated data Dout according to the interpolated position and the input distance to obtain an output interpolated signal Dout', wherein the expression is
Dout'(n+1)＝[Dout(Mn+1)-Dout(Mn)]·Ln+Dout(Mn)
The comparison process is shown in fig. 4, and specifically includes: with Kx_out(n) is a reference and Kx_inAre compared. Kx_inCounting by n' (0-4095), Kx_outCounting by n (0-4095) when Kx_in(n')＜Kx_outWhen (n), K is performedx_inA read operation of (n' + 1); when K isx_in(n')＞Kx_out(n) for FIFO, K is performedx_outA read operation of (n + 1); when K isx_in(n')＝Kx_out(n) for storing data and FIFO of data, K is performedx_in(n' +1) and Kx_outAnd (n +1) reading operation. When reading the FIFO, the data are read out in sequence according to the mode of input first and output first, and then the next round of comparison is carried out.
In this embodiment, the computation efficiency of the FPGA performing the search interpolation for 4096 points in data size is 0.2, that is, 5T clock cycles are required to complete the interpolation, so that five interpolation modules need to be instantiated to perform parallel interpolation processing to save the time for data processing, and the interpolation processing is performed between the five interpolation modules in a ping-pong manner, which can approximately achieve full-flow, so that the computation efficiency is approximately 1, thereby increasing the processing speed and reducing the processing time.
Thirdly, a multi-path data integration module;
and the multi-path data integration module integrates the interpolation results output by the distance and azimuth interpolation processing into one path respectively for output.
A timing diagram for distance versus data integration is shown in fig. 5. As can be seen from the figure, the data output by the two interpolation processing modules are sent to the data integration module in a time-sharing manner.
An orientation data integration timing diagram is shown in fig. 6. As can be seen from the figure, the data output by the five interpolation processing modules are sent to the data integration module in a time-sharing manner.
After the interpolation processing is completed, radar echo data which are distributed in a rectangular mode in a spatial domain can be obtained, and a foundation is laid for the subsequent PFA processing.
The foregoing detailed description is provided for the purpose of illustration and description, and is not intended to limit the scope of the claims. The technical solutions of the present invention obtained by any simple modification or replacement based on the technical solutions of the present invention, which are obtained by those skilled in the art, fall within the scope of the present invention.
Claims (7)
1. A two-dimensional interpolation module in the image processing process is characterized by comprising a multi-path data distribution module, an interpolation module and a multi-path data integration module:
the multi-path data distribution module comprises a multi-path distance direction data distribution module and a multi-path direction data distribution module;
the multi-path distance is transmitted to the data distribution module: dividing the preprocessed input data into multiple channels, outputting in a time-sharing manner, and sending the stream into parallel distance interpolation processing modules;
the multi-way azimuth data distribution module: dividing data subjected to distance data interpolation into multiple channels, outputting in a time-sharing manner, and sending running water into parallel azimuth interpolation processing modules;
an interpolation module: the system comprises a distance direction interpolation module and a direction interpolation module; respectively calculating distance direction interpolation positions and azimuth direction interpolation positions and interpolating;
and the multi-path data integration module integrates the interpolation results output by the distance and azimuth interpolation processing into one path respectively for output.
2. The two-dimensional interpolation module of claim 1, wherein the distance direction interpolation module calculates the distance direction interpolation position by using a derivation method.
3. A two-dimensional interpolation module in an image processing process according to claim 2, wherein the distance direction interpolation module is:
interpolation position X is
Will interpolate position XnDecomposed into integer parts MnAnd a fractional part LnThen, then
Outputting interpolated signal Dout expressed as
Dout(n+1)＝[Din(Mn+1)-Din(Mn)]·Ln+Din(Mn)
n is the number of data blocks; din is an input radar echo signal; initial value K of distance direction data before and after interpolationy_in0、Ky_out0And an incremental value Δ Ky_in、ΔKy_outAnd outputs a signal Dout interpolated over a distance.
4. A two-dimensional interpolation module in an image processing process according to claim 1, wherein the azimuth interpolation module calculates the azimuth interpolation position by using a search method.
5. A two-dimensional interpolation module in an image processing process according to claim 4, wherein the azimuth interpolation module is:
will Kx_outThe 4096 data are sequentially summed with K from large to small or from small to largex_inThe nth data K is obtained by comparing the data in (1)x_out(n) at Kx_inA position in the sequence which is the integer part M of the interpolated positionnAnd is obtained at Kx_out(n) left side data Kx_in(Mn) And data K on the rightx_in(Mn+1)；
After the interpolation position M and the corresponding data are obtained, the fractional part L of the interpolation position needs to be calculated, and then
Estimating according to the interpolation position M and the data Dout interpolated by the distance direction to obtain an interpolated signal Dout', wherein the expression is
Dout'(n+1)＝[Dout(Mn+1)-Dout(Mn)]·Ln+Dout(Mn)。
6. The two-dimensional interpolation module in an image processing process of claim 1, wherein the distance distribution channels are the same as the distance interpolation modules in number; the number of the azimuth distributing channels is the same as that of the azimuth interpolation modules.
7. A two-dimensional interpolation module for use in image processing as claimed in claim 1, wherein the module is based on operation on an array of field programmable logic gates.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105223572A (en) * | 2015-09-14 | 2016-01-06 | 北京航空航天大学 | A kind of positive forward sight Bistatic SAR image processing method based on PFA algorithm |
| CN105866774A (en) * | 2016-03-23 | 2016-08-17 | 南京航空航天大学 | FPGA implementation method for polar coordinate format imaging algorithm of chirp signal |
| CN108120980A (en) * | 2017-12-13 | 2018-06-05 | 南京航空航天大学 | A kind of implementation method of the FPGA of satellite-borne SAR multi-modal imaging signal processing algorithm |
| CN109932718A (en) * | 2019-03-11 | 2019-06-25 | 南京航空航天大学 | The circular path that multi-rotor unmanned aerial vehicle carries looks around SAR full aperture imaging method |
-
2019
- 2019-08-06 CN CN201910719523.4A patent/CN112346057B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105223572A (en) * | 2015-09-14 | 2016-01-06 | 北京航空航天大学 | A kind of positive forward sight Bistatic SAR image processing method based on PFA algorithm |
| CN105866774A (en) * | 2016-03-23 | 2016-08-17 | 南京航空航天大学 | FPGA implementation method for polar coordinate format imaging algorithm of chirp signal |
| CN108120980A (en) * | 2017-12-13 | 2018-06-05 | 南京航空航天大学 | A kind of implementation method of the FPGA of satellite-borne SAR multi-modal imaging signal processing algorithm |
| CN109932718A (en) * | 2019-03-11 | 2019-06-25 | 南京航空航天大学 | The circular path that multi-rotor unmanned aerial vehicle carries looks around SAR full aperture imaging method |
Non-Patent Citations (8)
| Title |
|---|
| 何静;侯新宇;王保平;: "ISAR成像中PFA算法在MTRC中的应用" * |
| 孙进平;白霞;毛士艺;: "聚束模式双基地SAR极坐标格式成像算法研究" * |
| 朱小鹏;张群;李宏伟;: "基于双基地ISAR的极坐标格式算法及其改进算法" * |
| 李威 等: "一种SAR极坐标格式成像算法的FPGA实现" * |
| 李威: "基于FPGA的SAR实时处理技术实现" * |
| 杨志富: "SAR/InSAR高速非平稳实时成像处理" * |
| 石佳宁: "基于FPGA的聚束SAR成像处理研究" * |
| 胡晓琛;李威;朱岱寅;崔爱欣;: "基于FPGA的微型SAR成像信号处理技术" * |
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