CA2579898C - Method for the processing and representing of ground images obtained by synthetic aperture radar systems (sar) - Google Patents
Method for the processing and representing of ground images obtained by synthetic aperture radar systems (sar) Download PDFInfo
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- CA2579898C CA2579898C CA2579898A CA2579898A CA2579898C CA 2579898 C CA2579898 C CA 2579898C CA 2579898 A CA2579898 A CA 2579898A CA 2579898 A CA2579898 A CA 2579898A CA 2579898 C CA2579898 C CA 2579898C
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/91—Radar or analogous systems specially adapted for specific applications for traffic control
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
- G01S13/9021—SAR image post-processing techniques
- G01S13/9023—SAR image post-processing techniques combined with interferometric techniques
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
- G01S13/9021—SAR image post-processing techniques
- G01S13/9029—SAR image post-processing techniques specially adapted for moving target detection within a single SAR image or within multiple SAR images taken at the same time
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/91—Radar or analogous systems specially adapted for specific applications for traffic control
- G01S13/92—Radar or analogous systems specially adapted for specific applications for traffic control for velocity measurement
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- Radar, Positioning & Navigation (AREA)
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- General Physics & Mathematics (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
For the detecting of moving vehicles by means of airplane- or space-based synthetic aperture radar systems (SAR), a known traffic route of a map, which is given by geographic coordinates and altitudes, is first converted into azimuth/range coordinates of the SAR radar image. The hypothetical radial speed (v r) of each image point of vehicles of potential relevance is determined from the distance to a traffic route in the azimuth direction, and the appertaining vehicle image position is determined by azimuth projection onto the respective traffic route. From this hypothetical vehicle radial speed, a first focusing parameter .DELTA.fDC is derived in dependence on the radar parameters. From the hypothetical vehicle radial speed, the angle of incidence of the radar beam onto the surface of the earth and the angle between the respective traffic route and the flight path of the radar sensor, the hypothetical vehicle azimuth speed (v a) is derived and, therefrom, by inclusion of the flight path of the radar sensor and the radar parameters, a second focusing parameter .DELTA.FM is derived. The two focusing parameters .DELTA.fDC and .DELTA.FM are used for exact adjustment of the SAR focusing to the moving object.
Application for the detecting of traffic flows and the representation of traffic flows.
Application for the detecting of traffic flows and the representation of traffic flows.
Description
The present invention relates to a method for the processing and representing of ground images obtained by airplane- or space-based synthetic aperture radar sensor systems (SAR).
Synthetic aperture radar (SAR) is used for remote sensing from space or from an airplane. In most cases where remote sensing is performed for civil uses, the stationary surface of the earth is imaged, Future space-based radar systems will have a sufficiently high resolution for imaging also individual vehicles. When using two or more antennae arranged at a mutual spatial distance in flight direction, the object will be observed at slightly different times, rendering it possible to detect a moving object and to measure its speed. The speed can be derived from the interferometric phase difference (I) AT.I = 21E `Tl BATT
a VSAR
of the SAR images obtained by means of the two antennae. In the above equation x represents the wavelength of the radar, BAT, represents the distance between the two antennae in flight direction, VSAR represents the speed of the SAR system, and yr represents the speed of the object in the radial direction relative to the flight path of the radar.
Due to the limitation of the observed phase to the interval [-1800, 180 ], the measurement of the speed can be performed merely with a certain ambivalence. Both effects, i.e. the phase and the speed-dependent displacement which is still to be described later on, will together yield good indicators to the speed of the object.
Synthetic aperture radar (SAR) is used for remote sensing from space or from an airplane. In most cases where remote sensing is performed for civil uses, the stationary surface of the earth is imaged, Future space-based radar systems will have a sufficiently high resolution for imaging also individual vehicles. When using two or more antennae arranged at a mutual spatial distance in flight direction, the object will be observed at slightly different times, rendering it possible to detect a moving object and to measure its speed. The speed can be derived from the interferometric phase difference (I) AT.I = 21E `Tl BATT
a VSAR
of the SAR images obtained by means of the two antennae. In the above equation x represents the wavelength of the radar, BAT, represents the distance between the two antennae in flight direction, VSAR represents the speed of the SAR system, and yr represents the speed of the object in the radial direction relative to the flight path of the radar.
Due to the limitation of the observed phase to the interval [-1800, 180 ], the measurement of the speed can be performed merely with a certain ambivalence. Both effects, i.e. the phase and the speed-dependent displacement which is still to be described later on, will together yield good indicators to the speed of the object.
However, the signals reflected by the vehicles are relatively weak so that their detection and measurement against the background noise (clutter) is correspondingly difficult, s Synthetic aperture radar makes use of the movement of the antenna along a known flight path in order to achieve a larger aperture and therefore a higher resolution. When, now, during the time of pick-up by the antenna, the to-be-Imaged object is moving, this gives rise to several disturbing influences:
a) A movement component yr of the object in the direction of the connecting line between sensor and object generates, in the SAR image, a displacement Da of the object in flight direction. A vehicle moving on a road is thus imaged at a position off the road. Since the backscatter signal as 1s caused by the buildings, woods and fields predominantly found off the road, may be in a magnitude as high as that of the signal of the vehicle, the vehicle will be detectable only with difficulties. The displacement can also be explained by a shifted Doppler spectrum of the moving object relative to the spectrum of the stationary object. Due to the lacking band limitation and due to the scanning of the Doppler spectrum with the radar pulse repetition frequency, different speeds will be ambiguously imaged on the same site.
b) In case of an SAR focusing set for stationary objects, the shifted Doppler spectrum may easily cause false "ghost images" (ambiguities). Also this effect will cause a weakening of the signal because the received energy of the vehicle is distributed onto two widely distanced image points. If, during the time of pick-up by the antenna, the vehicle moves away by more than one resolution cell, the additional "range migration" will cause a deterioration of the azimuth and range focusing, and the object will appear 3 0 still darker.
c) Under the effect of a movement component va of the object in the flight direction of the antenna, the azimuth frequency modulation rate FM - which is Important for the SAR focusing - will be changed, thus causing a blurring of the point response in flight direction.
With regard to the above, Fig. 1 schematically illustrates the vehicle s misrepresentations in a usual conventional SAR Image. As schematically outlined in this Figure, a moving vehicle imaged by Synthetic aperture radar is displaced in flight direction relative to the stationary background, is blurred in the azimuth direction and is possibly imaged several times (ambiguity).
For the above reasons, in radar systems which have been designed for imaging stationary objects, the processing of the data and the detection of vehicles is impeded by considerable difficulties.
is Therefore, and also because of the relatively low resolution of present-day civil radar systems, the detection of moving vehicles - also referred to as GMTI (Ground Moving Target Indication) - is of highly topical relevance on the military sector. On this sector, use is made of airplane-based radar systems which have been optimized for GMTI. To facilitate the detection of moving objects, these systems have e.g. a plurality of antennae, a considerably increased pulse repetition frequency and a stronger transmitting power.
To make it possible to locate, in a radar field, the signal of a vehicle which is weak in comparison with the background, the vehicle has to be focused in an optimum manner, i.e. its whole energy should be concentrated onto one image point. Because of the above mentioned effects, however, it is necessitated that the position, the speed and the direction of the vehicle are known already before the processing.
A relatively obvious but very complex solution to this problem would reside in generating, in a first step, respectively one image for all possible combinations of radial and azimuth speeds (v,- and va) and, in a second step, searching the vehicles in the resultant stack of images. However, the number of images required for this approach could be in the magnitude of several hundreds. Generating these images would require massive computational expenditure, and the numerical processing to be further performed on these images, e.g. the detection of a vehicle in this stack of images, is complicated as well. Also a visual evaluation of such a large quantity of image is unrealistic.
To sum up, it is to be stated that the detection of moving objects in SAR
io images is very difficult because such objects will appear shifted as compared to stationary objects and because, due to their self-focusing, they will be focused in a non-sharp manner.
Thus, it is an object of the present invention to detect moving vehicles, particularly road and rail vehicles, by means of airplane- or space-based synthetic aperture radar sensor systems (SAR) in a better manner while requiring less expenditure regarding personnel and technical apparatus.
According to the invention, which relates to a method for the processing and representing of ground images obtained by airplane- or space-based synthetic aperture radar sensor systems (SAR), the above object is achieved in that a known traffic route of a map, which is given by geographic coordinates and altitudes, is converted into azimuth/range coordinates of the SAR radar image, that the hypothetical radial speed of each image point of vehicles of potential relevance is determined from the distance of the image point to a traffic route in the azimuth direction and the appertaining vehicle image position is determined by azimuth projection onto the respective traffic route, and that, from this hypothetical vehicle radial speed, a first focusing parameter AFDC for the focusing is derived in dependence on the radar parameters, and that, from the hypothetical vehicle radial speed, the angle of incidence of the radar beam onto the surface of the earth and the angle between the respective traffic route and the flight path of the radar sensor, the hypothetical vehicle azimuth speed is derived and, therefrom, by inclusion of the flight path of the radar sensor and the radar parameters, a second focusing parameter LFM is derived, and that the two focusing parameters AfDC and dFM derived from the hypothetical radial and azimuth speeds are plotted in a matrix and are used 5 for exact adjustment of the SAR focusing to the moving object.
The invention utilizes the already existing knowledge about the traffic route for a precise and effective focusing as well as for a form of representation which considerably facilitates the interpretation of the SAR radar images.
1.0 The invention is distinguished in that digital maps of traffic routes, i.e.
particularly digital road maps, railroad maps or river route maps, will be included into the SAR focusing. In doing so, the traffic route is transformed into the radar image geometry. Then, the vehicle radar speed of each image point is determined on the basis of the distance from the image point to the traffic route in the azimuth direction and of the appertaining vehicle position by azimuth projection onto the road. Subsequently, the azimuth speed is detected on the basis of the above radial speed and the road angle. Finally, on the basis of the detected radial and azimuth speeds, there is performed a precise and efficient focusing of the individual image point which corresponds to a moving object, i.e. a moving vehicle.
The advantages of the method performed according to the present invention reside primarily in that only one SAR image has to be generated and to be searched for vehicles, thus accomplishing considerable time-saving and simplification. Each vehicle is subjected to optimum focusing, with a resultant increase of the vehicle-detection probability. The clutter for quickly moving objects will be reduced In contrast and for certain speed ranges will become darker, again with a resultant increase of the vehicle-detection probability. Finally, when using of the method of the present invention, the image can be easily and quickly be interpreted by an evaluating person.
a) A movement component yr of the object in the direction of the connecting line between sensor and object generates, in the SAR image, a displacement Da of the object in flight direction. A vehicle moving on a road is thus imaged at a position off the road. Since the backscatter signal as 1s caused by the buildings, woods and fields predominantly found off the road, may be in a magnitude as high as that of the signal of the vehicle, the vehicle will be detectable only with difficulties. The displacement can also be explained by a shifted Doppler spectrum of the moving object relative to the spectrum of the stationary object. Due to the lacking band limitation and due to the scanning of the Doppler spectrum with the radar pulse repetition frequency, different speeds will be ambiguously imaged on the same site.
b) In case of an SAR focusing set for stationary objects, the shifted Doppler spectrum may easily cause false "ghost images" (ambiguities). Also this effect will cause a weakening of the signal because the received energy of the vehicle is distributed onto two widely distanced image points. If, during the time of pick-up by the antenna, the vehicle moves away by more than one resolution cell, the additional "range migration" will cause a deterioration of the azimuth and range focusing, and the object will appear 3 0 still darker.
c) Under the effect of a movement component va of the object in the flight direction of the antenna, the azimuth frequency modulation rate FM - which is Important for the SAR focusing - will be changed, thus causing a blurring of the point response in flight direction.
With regard to the above, Fig. 1 schematically illustrates the vehicle s misrepresentations in a usual conventional SAR Image. As schematically outlined in this Figure, a moving vehicle imaged by Synthetic aperture radar is displaced in flight direction relative to the stationary background, is blurred in the azimuth direction and is possibly imaged several times (ambiguity).
For the above reasons, in radar systems which have been designed for imaging stationary objects, the processing of the data and the detection of vehicles is impeded by considerable difficulties.
is Therefore, and also because of the relatively low resolution of present-day civil radar systems, the detection of moving vehicles - also referred to as GMTI (Ground Moving Target Indication) - is of highly topical relevance on the military sector. On this sector, use is made of airplane-based radar systems which have been optimized for GMTI. To facilitate the detection of moving objects, these systems have e.g. a plurality of antennae, a considerably increased pulse repetition frequency and a stronger transmitting power.
To make it possible to locate, in a radar field, the signal of a vehicle which is weak in comparison with the background, the vehicle has to be focused in an optimum manner, i.e. its whole energy should be concentrated onto one image point. Because of the above mentioned effects, however, it is necessitated that the position, the speed and the direction of the vehicle are known already before the processing.
A relatively obvious but very complex solution to this problem would reside in generating, in a first step, respectively one image for all possible combinations of radial and azimuth speeds (v,- and va) and, in a second step, searching the vehicles in the resultant stack of images. However, the number of images required for this approach could be in the magnitude of several hundreds. Generating these images would require massive computational expenditure, and the numerical processing to be further performed on these images, e.g. the detection of a vehicle in this stack of images, is complicated as well. Also a visual evaluation of such a large quantity of image is unrealistic.
To sum up, it is to be stated that the detection of moving objects in SAR
io images is very difficult because such objects will appear shifted as compared to stationary objects and because, due to their self-focusing, they will be focused in a non-sharp manner.
Thus, it is an object of the present invention to detect moving vehicles, particularly road and rail vehicles, by means of airplane- or space-based synthetic aperture radar sensor systems (SAR) in a better manner while requiring less expenditure regarding personnel and technical apparatus.
According to the invention, which relates to a method for the processing and representing of ground images obtained by airplane- or space-based synthetic aperture radar sensor systems (SAR), the above object is achieved in that a known traffic route of a map, which is given by geographic coordinates and altitudes, is converted into azimuth/range coordinates of the SAR radar image, that the hypothetical radial speed of each image point of vehicles of potential relevance is determined from the distance of the image point to a traffic route in the azimuth direction and the appertaining vehicle image position is determined by azimuth projection onto the respective traffic route, and that, from this hypothetical vehicle radial speed, a first focusing parameter AFDC for the focusing is derived in dependence on the radar parameters, and that, from the hypothetical vehicle radial speed, the angle of incidence of the radar beam onto the surface of the earth and the angle between the respective traffic route and the flight path of the radar sensor, the hypothetical vehicle azimuth speed is derived and, therefrom, by inclusion of the flight path of the radar sensor and the radar parameters, a second focusing parameter LFM is derived, and that the two focusing parameters AfDC and dFM derived from the hypothetical radial and azimuth speeds are plotted in a matrix and are used 5 for exact adjustment of the SAR focusing to the moving object.
The invention utilizes the already existing knowledge about the traffic route for a precise and effective focusing as well as for a form of representation which considerably facilitates the interpretation of the SAR radar images.
1.0 The invention is distinguished in that digital maps of traffic routes, i.e.
particularly digital road maps, railroad maps or river route maps, will be included into the SAR focusing. In doing so, the traffic route is transformed into the radar image geometry. Then, the vehicle radar speed of each image point is determined on the basis of the distance from the image point to the traffic route in the azimuth direction and of the appertaining vehicle position by azimuth projection onto the road. Subsequently, the azimuth speed is detected on the basis of the above radial speed and the road angle. Finally, on the basis of the detected radial and azimuth speeds, there is performed a precise and efficient focusing of the individual image point which corresponds to a moving object, i.e. a moving vehicle.
The advantages of the method performed according to the present invention reside primarily in that only one SAR image has to be generated and to be searched for vehicles, thus accomplishing considerable time-saving and simplification. Each vehicle is subjected to optimum focusing, with a resultant increase of the vehicle-detection probability. The clutter for quickly moving objects will be reduced In contrast and for certain speed ranges will become darker, again with a resultant increase of the vehicle-detection probability. Finally, when using of the method of the present invention, the image can be easily and quickly be interpreted by an evaluating person.
Further advantageous and suitable embodiments of the invention are indicated in the claims directly or indirectly depending on claim 1.
The focusing of the individual image point or its surroundings under consideration of the radial and azimuth speeds can be advantageously performed in the time domain using an adaptive time domain correlator.
Alternatively, using standard SAR processors, the focusing of a plurality of images with different speed parameters (vr,v,) can be performed together in advance, while only image regions near roads will be focused. Then, there will be performed a combination into an image, wherein each image point is taken from the image which corresponds to the hypothetical radial and azimuth speeds.
According to a further alternative, a prefocusing of the image by use of a modified standard SAR processor and a refocusing by use of a position-adaptive correction filter can be performed in the time domain. The modification of a standard SAR processor consists in the internal replication of the azimuth spectrum.
_ A further embodiment of the invention resides in the representation only of the road route, i.e. not of the whole picture, with speed contours for visual evaluations by persons.
Advantageously, one can obtain a colored representation of the interferometric SAR image with overlying colored speed structures for multi-channel systems (ATI - Along-Track Interfermometry).
Further, the method of the present invention advantageously allows for a colored representation of the SAR image with overlying colored speed structures for DPCA (Displaced Phase Center Antenna) systems, i.e.
systems comprising an antenna with two or more shifted phase centers, The method of the present invention is applicable in a particularly advantageous manner in the detection, use and marketing of traffic data for scientific, economical and safety-related purposes and in the generating of easily surveyable images of traffic flows.
The invention will be explained in greater detail hereunder with reference to the accompanying drawings and diagrams. Shown therein is the following:
Fig. 1 shows the already described schematic representation for pointing 1.0 out the difficulties occurring in the imaging of moving vehicles by means of normal conventional SAR systems, which difficulties reside in that the image points representing the vehicles are displaced in flight direction relative to the stationary background, are blurred in the azimuth and are possibly rendered by multiple images 2s (ambiguity);
Fig. 2 shows a schematic representation for visualizing the map-controlled speed-dependent SAR focusing according to the method of the present invention;
Fig. 3 shows a schematic representation of an SAR image with ISO speeds subjected to speed-dependent focusing according to the method of the present invention;
Fig. 4 shows a flow chart of a speed-dependent SAR process performed according to the method of the present invention with subsequent SAR processing in a first variant (variant a) using a visualization by means of an adaptive time domain correlator;
Fig. 5 shows a flow chart of a speed-dependent SAR process performed according to the method of the present invention with subsequent SAR processing in a second variant (variant b) using a visualization by means of standard SAR processor;
The focusing of the individual image point or its surroundings under consideration of the radial and azimuth speeds can be advantageously performed in the time domain using an adaptive time domain correlator.
Alternatively, using standard SAR processors, the focusing of a plurality of images with different speed parameters (vr,v,) can be performed together in advance, while only image regions near roads will be focused. Then, there will be performed a combination into an image, wherein each image point is taken from the image which corresponds to the hypothetical radial and azimuth speeds.
According to a further alternative, a prefocusing of the image by use of a modified standard SAR processor and a refocusing by use of a position-adaptive correction filter can be performed in the time domain. The modification of a standard SAR processor consists in the internal replication of the azimuth spectrum.
_ A further embodiment of the invention resides in the representation only of the road route, i.e. not of the whole picture, with speed contours for visual evaluations by persons.
Advantageously, one can obtain a colored representation of the interferometric SAR image with overlying colored speed structures for multi-channel systems (ATI - Along-Track Interfermometry).
Further, the method of the present invention advantageously allows for a colored representation of the SAR image with overlying colored speed structures for DPCA (Displaced Phase Center Antenna) systems, i.e.
systems comprising an antenna with two or more shifted phase centers, The method of the present invention is applicable in a particularly advantageous manner in the detection, use and marketing of traffic data for scientific, economical and safety-related purposes and in the generating of easily surveyable images of traffic flows.
The invention will be explained in greater detail hereunder with reference to the accompanying drawings and diagrams. Shown therein is the following:
Fig. 1 shows the already described schematic representation for pointing 1.0 out the difficulties occurring in the imaging of moving vehicles by means of normal conventional SAR systems, which difficulties reside in that the image points representing the vehicles are displaced in flight direction relative to the stationary background, are blurred in the azimuth and are possibly rendered by multiple images 2s (ambiguity);
Fig. 2 shows a schematic representation for visualizing the map-controlled speed-dependent SAR focusing according to the method of the present invention;
Fig. 3 shows a schematic representation of an SAR image with ISO speeds subjected to speed-dependent focusing according to the method of the present invention;
Fig. 4 shows a flow chart of a speed-dependent SAR process performed according to the method of the present invention with subsequent SAR processing in a first variant (variant a) using a visualization by means of an adaptive time domain correlator;
Fig. 5 shows a flow chart of a speed-dependent SAR process performed according to the method of the present invention with subsequent SAR processing in a second variant (variant b) using a visualization by means of standard SAR processor;
Fig. 6 shows a flow chart of a speed-dependent SAR process performed according to the method of the present invention with subsequent SAR processing in a third variant (variant c) using a visualization by s means of standard SAR processor and adaptive refocusing; and Fig. 7 shows four examples of images rendered by a prototype of a processor, Fig. 7a showing a conventional SAR image presenting a road and superimposed ISO speed lines, Fig. 7b showing a conventional SAR image of the relevant region image presenting a road and superimposed ISO speed lines, Fig. 7c showing an SAR
image with speed-adaptive focusing, presenting a road and superimposed ISO speed lines, and Fig. 7d showing an SAR Image with speed-adaptive focusing, with superimposed interferometric 1s phase, road and ISO speed lines, the interferometric phase being superimposed in colored representation.
The principle of the method for the processing and representing of the SAR
images according to the present invention will be demonstrated and explained hereunder with reference to Fig. 2. The processing is considerably simplified by the novel combination of two approaches.
The road network is known. Thus, according to the first approach, the space of solutions can be considerably restricted. According to the present invention, this is performed in that the road route, given by geographic coordinates and altitudes { (x, y, z), ... ; , is converted into the azimuth/range coordinates of the radar image { (a, r), ... I.
According to a second approach, the SAR focusing is controlled by reverse projection. In this approach, the treatment each possibly relevant image point will be based on the hypothesis that this image point is the representation of a vehicle. First, there is determined the distance a from the point to the assumed traffic route (e.g. road, rail) in the flight direction of the airplane- or space-based SAR sensor. From this distance, both the position of the vehicle on the road and its radial speed Vr can be derived.
Here, R denotes the distance between the antenna and the point, and VsAR
denotes the speed of the SAR antenna:
Aa yr = R 1'.C-0R
For focusing, it easily possible to derive, from the hypothetical radial speed yr and in dependence on the radar parameters, the proportional correction parameter AMC, i.e. the displacement of the azimuth spectrum as compared to the stationary earth. With the aid of the angle of incidence 8 of the radar beam onto the earth's surface and the angle a between the road and the flight path of the radar sensor, one can determine, from the radial speed v,, also the hypothetical azimuth speed v3 and, therefrom, with the aid of the flight path and the radar parameters of the second focusing parameters, one can determine the change of the frequency modulation rate 1FM. However, this will not be feasible in case of movements which are nearly parallel to the fight path with a _= 0.
The two parameters dfDC and AFM derived from.the hypothetical radial and azimuth speeds yr and v, are plotted in a matrix and are used for exact adjustment of the SAR focusing to the moving object. Thereby, it is safeguarded that the hypothetical vehicle will be optimally focused. In case that the above hypothesis does not hold true, he. the image point does not include a vehicle, the stationary background is defocused, which, however, is not relevant for the detection of the vehicle. In the map, there have also been marked those regions which need not be processed at all because the displacement towards the closest road would correspond to an unrealistic speed.
The focusing parameter map is generated according to the flow charts outlined in Figs. 4 to 6 in the manner explained hereunder:
The road route is extracted from a digital road route database in the form of segments or a three-dimensional sequence of points {x, y, z}.
5 The segments and the sequence of points { (x, y, z), ... }, respectively, are transformed into the azimuth/range radar coordinate system { (as, r5i) ... }
From the segments, there is interpolated a nearly continuous course zo for each pixel of the radar image. This road route will finally be additionally superimposed to the radar image for visual evaluation.
For each pixel in the range, the maximum range of displacement in the azimuth direction is now determined on the basis of an assumed is maximum vehicle speed Vmax, This maximum displacement range depends on the angle of incidence 6 and the local road angle a:
Lt = V,rti,.Y sin(a)cos(q) R
V SAR
For each roadway position {as, rj, the vehicle can be imaged only into the range { [a.-Damax, aE+iam ] , r.).
Now, for each possible image point {a, r} within the range { [a3-Damax, ao oama,,] , rs}, the radial speed yr and the azimuth speed vv are computed:
a-as V'a =
tan a = cos 6 Obtained from these parameters are the focusing film parameters AFDC and LFM which will be used to adjust the SAR processor for the speed which is to be expected, This pair of focusing parameters is computed for each possibly relevant image point near the road, The parameter AFDC can be derived in a simple manner from the radial speed võ as follows:
AJDC J AV, wherein h is the wavelength of the radar.
The FM rate of a constantly moving vehicle having the azimuth speed component ve at a linear flight path of the SAR is computed as:
z 2 2 FAlr = --- (v$AR - vn) = -2 V,An --(v,2 - 2vsau va) =FM, + AFAM
a AR AR
so that the additional FM rate caused by the vehicle will be.
LFM = -R (v2 - 2i.san vQ ) If the vehicle does not move linearly with constant speed, i.e. if the vehicle is accelerated in a radial direction relative to the radar antenna, this will result in further influences on the frequency modulation rate AFM, with the consequence that the image of the vehicle will be defocused in the azimuth.
If such an acceleration component is caused by the vehicle's following a curved route at constant speed, the resultant defocusing can be compensated for by means of a slight modification of the method. For this purpose, using a numerical derivation of the radial component of the speed, the radial acceleration is computed:
__ dy, yr dt This radial component will effect a further correction of the frequency modulation rate AFM,,C. For vehicles undergoing a radial change of speed, i.e. a radial acceleration v,. relative to the sensor, the acceleration parameter will be included In the quadratic distance function, resulting in a further influence on the FM rate:
t0 or a,:~ _ ~ v, The frequency modulation rate correction to be considered in the focusing comprises the correction for the azimuth speed and the correction for the radial acceleration:
AFJ;1~S02-,r, = 4F + AFS'~fy Q,, At the same time, the extreme values AfDC_m,,, AFDC ma,., dx'M,,,,,r, and AFKõax are obtained for the whole course of the road.
For the realization of the subsequent SAR processing, three variants a), b) and c) are proposed according the invention, to be described hereunder with reference to Figs. 4 to 6.
Variant a): Use is made of a special time range correlator which, for focusing each individual image point, will correlate the SAR raw data using a two-dimensional correlation core, According to the invention, this correlation core will be adapted for each image point with the aid of the two 3o focusing parameters AFDC and AFM and thus allow for an optimum movement-adaptive image of the road and of the vehicles driving on it.
From the potentially relevant speeds and positions, a control mask is computed, To save time, the image will be focused only for those areas which have been marked in the control mask. This image is mathematically exact and thus optimally focused..This variant is schematically shown in the flow chart of Fig. 4. Depending on the prevailing circumstances, the computation may take a longer time than the generating of a plurality of images by means of standard SAR processors which is described hereunder as variant b).
Variant b): In this variant, standard SAR processors are used. The range [afDCmin, dfDCmax! is discretized into N intervals, and the range [l1FMmin, ,4FMmax1 is discretized into M intervals, the interval boundaries being selected in such a manner that the processing errors caused by the is discretizing will be tolerable. The average values of the intervals are orthogonally entered into a two-dimensional discretizing table. For each element of the discretizing table, which has a size Z = N x M, the matrix of the focusing parameters is searched for pairs of values which belong into this discretizing interval. The result resides in Z control masks which will instruct the SAR processor as to what image portions have to be processed at all. As Fig. 5 shows, Z images covering all required Z combinations of focusing parameters, are processed in Z standard SAR processors which are connected in parallel or are arranged behind each other in the computer. It is advantageous if a standard SAR processor is slightly modified. By such a modified standard SAR processor, those processing steps which are independent from the parameters AMC and LFM will be carried out only once, and all subsequent processing steps will be carried out Z times with adapted parameters. The processor will process for each image according to the invention only the image points marked in the control mask, thus saving considerable computational time. Now, there have been obtained Z partial images which, with the aid of the Z control masks, will be assembled again into one image. The result of this process is an image of the road and its surroundings as obtained by variant a) with the time domain correlator.
Variant c): A standard SAR processor will process the scene using the average focusing parameters iDC and 6FM, i.e. the parameters normally related to the stationary scene, which have been taken from the discretizing s table. In this first step, the focusing artifacts caused by the movement will be tolerated. Additionally, a modification is performed which resides in that, prior to the focusing, the signal spectrum is replicated in azimuth to the effect that also moving objects are correctly processed by the processor with regard to their spectrum and their range migration. The azimuth 1.0 bandwidth of the processor will be correspondingly widely dimensioned for the following processing. Thus, the focused image includes the image of vehicles and clutter as well as their spectrally and spatially shifted versions.
Then, in a position-adaptive post-processing step, the remaining movement unsharpness LFM is corrected in the azimuth direction, and the azimuth 1s spectrum of the expected image is filtered out. The filtering can be performed in the time domain or by fast convolution. Also in this variant, a control mask is used for processing only the necessary image portions. Fig.
6 shows a schematic flowchart of this speed-adaptive SAR process performed according to the method of the invention, with subsequent SAR
20 processing according to variant c) by use of visualization with the aid of a standard SAR processor and adaptive refocusing.
For interferometric multi-antennae-systems, the computation of the control masks and of the speed-depedent parameters is carried out only once, and 25 the actual SAR processing is performed separately for each antenna channel of the system.
An advantageous embodiment of the method of the present invention resides in a novel representation of the image for the purposes of visual 30 evaluation. For this representation, both the road route and the lines of the same speed are superimposed onto the SAR Image generated according to the above description. The azimuth displacement for a constant speed V,so is computed, for each point of the road in the range, on the basis of the following equation:
Da = vsQ sin(a)cog(0) R
VSAR
These lines of identical speeds (ISO speed lines) are superimposed onto the SAR image like contour lines on a topographic map. Fig. 3 shows a schematic representation of an SAR image with speed-dependent focusing which is provided with ISO speed lines.
,13 In case of an interferometric SAR corresponding to along-track interfermo-metry (ATI), the lines will be plotted advantageously in colored representation corresponding to the expected interferometric phase. The SAR image will be generated from the two existing antenna channels and be is colored corresponding to the interferometric phase difference between the two channels. The visual evaluation will now be performed as follows: Bright points are assumed to represent vehicles, and their speeds will be estimated on the basis of the closest ISO speed lines. In case of ATI
processing, it is additionally provided that the color (= phase) of the point is compared to the color of the closest ISO speed line. Thus, if the speed derived from the displacement and the speed derived from the color coincide with each other, a very high likelihood exists that there really occurs a movement with this speed. Further, the problem of ambiguities can be eliminated if the speed ambiguity intervals of the phase and of the pulse repetition frequency are different.
An alternative method for along-track interfermometry (ATI) consists in the subtraction of the results of the two antenna channels, also referred to as DPCA (Displaced Phase Center Antenna). Here, not the phase difference but the difference of the complex images of both antennae is generated. In the ideal case, the stationary background (clutter) is eliminated in the process, and the moving vehicles will be maintained as bright points. Also this image is suitably represented with superimposed road routes and lines of identical speeds.
The thus generated image is much better suited for interpretation than a s standard SAR image focused with constant parameters or even just a stack of images because, here, only one band along the road has to be evaluated in a single image and the visual evaluation is supported by the speed contours.
In Fig. 7, four examples of images obtained from data of the Shuttle Radar Topography Mission (SRTM) are schematically illustrated. In the conventional standard SAR image according to Fig. 7a, the vehicles and the road can be made out only with difficulties. The superimposed ISO speed lines representing multiples of 50 km/h are already helpful in the 1s interpretation of the SAR image, Still more easily surveyable is the variant according to Fig. 7b wherein only the relevant range has been focused, while also saving computational time. Fig. 7c illustrates the overall SAR
image with exclusively speed-adaptive focusing and with superimposed ISO
speed lines. Thus, the stationary clutter in the region of the road has an ambiguous appearance. For certain speed ranges outside of the clutter spectrum, the vehicles are now visualized much brighter. In Fig. 7d, the SAR image and the ISO speed lines are colored with respect to their interferometric phase. In this manner, it is also possible to eliminate ambiguities.
image with speed-adaptive focusing, presenting a road and superimposed ISO speed lines, and Fig. 7d showing an SAR Image with speed-adaptive focusing, with superimposed interferometric 1s phase, road and ISO speed lines, the interferometric phase being superimposed in colored representation.
The principle of the method for the processing and representing of the SAR
images according to the present invention will be demonstrated and explained hereunder with reference to Fig. 2. The processing is considerably simplified by the novel combination of two approaches.
The road network is known. Thus, according to the first approach, the space of solutions can be considerably restricted. According to the present invention, this is performed in that the road route, given by geographic coordinates and altitudes { (x, y, z), ... ; , is converted into the azimuth/range coordinates of the radar image { (a, r), ... I.
According to a second approach, the SAR focusing is controlled by reverse projection. In this approach, the treatment each possibly relevant image point will be based on the hypothesis that this image point is the representation of a vehicle. First, there is determined the distance a from the point to the assumed traffic route (e.g. road, rail) in the flight direction of the airplane- or space-based SAR sensor. From this distance, both the position of the vehicle on the road and its radial speed Vr can be derived.
Here, R denotes the distance between the antenna and the point, and VsAR
denotes the speed of the SAR antenna:
Aa yr = R 1'.C-0R
For focusing, it easily possible to derive, from the hypothetical radial speed yr and in dependence on the radar parameters, the proportional correction parameter AMC, i.e. the displacement of the azimuth spectrum as compared to the stationary earth. With the aid of the angle of incidence 8 of the radar beam onto the earth's surface and the angle a between the road and the flight path of the radar sensor, one can determine, from the radial speed v,, also the hypothetical azimuth speed v3 and, therefrom, with the aid of the flight path and the radar parameters of the second focusing parameters, one can determine the change of the frequency modulation rate 1FM. However, this will not be feasible in case of movements which are nearly parallel to the fight path with a _= 0.
The two parameters dfDC and AFM derived from.the hypothetical radial and azimuth speeds yr and v, are plotted in a matrix and are used for exact adjustment of the SAR focusing to the moving object. Thereby, it is safeguarded that the hypothetical vehicle will be optimally focused. In case that the above hypothesis does not hold true, he. the image point does not include a vehicle, the stationary background is defocused, which, however, is not relevant for the detection of the vehicle. In the map, there have also been marked those regions which need not be processed at all because the displacement towards the closest road would correspond to an unrealistic speed.
The focusing parameter map is generated according to the flow charts outlined in Figs. 4 to 6 in the manner explained hereunder:
The road route is extracted from a digital road route database in the form of segments or a three-dimensional sequence of points {x, y, z}.
5 The segments and the sequence of points { (x, y, z), ... }, respectively, are transformed into the azimuth/range radar coordinate system { (as, r5i) ... }
From the segments, there is interpolated a nearly continuous course zo for each pixel of the radar image. This road route will finally be additionally superimposed to the radar image for visual evaluation.
For each pixel in the range, the maximum range of displacement in the azimuth direction is now determined on the basis of an assumed is maximum vehicle speed Vmax, This maximum displacement range depends on the angle of incidence 6 and the local road angle a:
Lt = V,rti,.Y sin(a)cos(q) R
V SAR
For each roadway position {as, rj, the vehicle can be imaged only into the range { [a.-Damax, aE+iam ] , r.).
Now, for each possible image point {a, r} within the range { [a3-Damax, ao oama,,] , rs}, the radial speed yr and the azimuth speed vv are computed:
a-as V'a =
tan a = cos 6 Obtained from these parameters are the focusing film parameters AFDC and LFM which will be used to adjust the SAR processor for the speed which is to be expected, This pair of focusing parameters is computed for each possibly relevant image point near the road, The parameter AFDC can be derived in a simple manner from the radial speed võ as follows:
AJDC J AV, wherein h is the wavelength of the radar.
The FM rate of a constantly moving vehicle having the azimuth speed component ve at a linear flight path of the SAR is computed as:
z 2 2 FAlr = --- (v$AR - vn) = -2 V,An --(v,2 - 2vsau va) =FM, + AFAM
a AR AR
so that the additional FM rate caused by the vehicle will be.
LFM = -R (v2 - 2i.san vQ ) If the vehicle does not move linearly with constant speed, i.e. if the vehicle is accelerated in a radial direction relative to the radar antenna, this will result in further influences on the frequency modulation rate AFM, with the consequence that the image of the vehicle will be defocused in the azimuth.
If such an acceleration component is caused by the vehicle's following a curved route at constant speed, the resultant defocusing can be compensated for by means of a slight modification of the method. For this purpose, using a numerical derivation of the radial component of the speed, the radial acceleration is computed:
__ dy, yr dt This radial component will effect a further correction of the frequency modulation rate AFM,,C. For vehicles undergoing a radial change of speed, i.e. a radial acceleration v,. relative to the sensor, the acceleration parameter will be included In the quadratic distance function, resulting in a further influence on the FM rate:
t0 or a,:~ _ ~ v, The frequency modulation rate correction to be considered in the focusing comprises the correction for the azimuth speed and the correction for the radial acceleration:
AFJ;1~S02-,r, = 4F + AFS'~fy Q,, At the same time, the extreme values AfDC_m,,, AFDC ma,., dx'M,,,,,r, and AFKõax are obtained for the whole course of the road.
For the realization of the subsequent SAR processing, three variants a), b) and c) are proposed according the invention, to be described hereunder with reference to Figs. 4 to 6.
Variant a): Use is made of a special time range correlator which, for focusing each individual image point, will correlate the SAR raw data using a two-dimensional correlation core, According to the invention, this correlation core will be adapted for each image point with the aid of the two 3o focusing parameters AFDC and AFM and thus allow for an optimum movement-adaptive image of the road and of the vehicles driving on it.
From the potentially relevant speeds and positions, a control mask is computed, To save time, the image will be focused only for those areas which have been marked in the control mask. This image is mathematically exact and thus optimally focused..This variant is schematically shown in the flow chart of Fig. 4. Depending on the prevailing circumstances, the computation may take a longer time than the generating of a plurality of images by means of standard SAR processors which is described hereunder as variant b).
Variant b): In this variant, standard SAR processors are used. The range [afDCmin, dfDCmax! is discretized into N intervals, and the range [l1FMmin, ,4FMmax1 is discretized into M intervals, the interval boundaries being selected in such a manner that the processing errors caused by the is discretizing will be tolerable. The average values of the intervals are orthogonally entered into a two-dimensional discretizing table. For each element of the discretizing table, which has a size Z = N x M, the matrix of the focusing parameters is searched for pairs of values which belong into this discretizing interval. The result resides in Z control masks which will instruct the SAR processor as to what image portions have to be processed at all. As Fig. 5 shows, Z images covering all required Z combinations of focusing parameters, are processed in Z standard SAR processors which are connected in parallel or are arranged behind each other in the computer. It is advantageous if a standard SAR processor is slightly modified. By such a modified standard SAR processor, those processing steps which are independent from the parameters AMC and LFM will be carried out only once, and all subsequent processing steps will be carried out Z times with adapted parameters. The processor will process for each image according to the invention only the image points marked in the control mask, thus saving considerable computational time. Now, there have been obtained Z partial images which, with the aid of the Z control masks, will be assembled again into one image. The result of this process is an image of the road and its surroundings as obtained by variant a) with the time domain correlator.
Variant c): A standard SAR processor will process the scene using the average focusing parameters iDC and 6FM, i.e. the parameters normally related to the stationary scene, which have been taken from the discretizing s table. In this first step, the focusing artifacts caused by the movement will be tolerated. Additionally, a modification is performed which resides in that, prior to the focusing, the signal spectrum is replicated in azimuth to the effect that also moving objects are correctly processed by the processor with regard to their spectrum and their range migration. The azimuth 1.0 bandwidth of the processor will be correspondingly widely dimensioned for the following processing. Thus, the focused image includes the image of vehicles and clutter as well as their spectrally and spatially shifted versions.
Then, in a position-adaptive post-processing step, the remaining movement unsharpness LFM is corrected in the azimuth direction, and the azimuth 1s spectrum of the expected image is filtered out. The filtering can be performed in the time domain or by fast convolution. Also in this variant, a control mask is used for processing only the necessary image portions. Fig.
6 shows a schematic flowchart of this speed-adaptive SAR process performed according to the method of the invention, with subsequent SAR
20 processing according to variant c) by use of visualization with the aid of a standard SAR processor and adaptive refocusing.
For interferometric multi-antennae-systems, the computation of the control masks and of the speed-depedent parameters is carried out only once, and 25 the actual SAR processing is performed separately for each antenna channel of the system.
An advantageous embodiment of the method of the present invention resides in a novel representation of the image for the purposes of visual 30 evaluation. For this representation, both the road route and the lines of the same speed are superimposed onto the SAR Image generated according to the above description. The azimuth displacement for a constant speed V,so is computed, for each point of the road in the range, on the basis of the following equation:
Da = vsQ sin(a)cog(0) R
VSAR
These lines of identical speeds (ISO speed lines) are superimposed onto the SAR image like contour lines on a topographic map. Fig. 3 shows a schematic representation of an SAR image with speed-dependent focusing which is provided with ISO speed lines.
,13 In case of an interferometric SAR corresponding to along-track interfermo-metry (ATI), the lines will be plotted advantageously in colored representation corresponding to the expected interferometric phase. The SAR image will be generated from the two existing antenna channels and be is colored corresponding to the interferometric phase difference between the two channels. The visual evaluation will now be performed as follows: Bright points are assumed to represent vehicles, and their speeds will be estimated on the basis of the closest ISO speed lines. In case of ATI
processing, it is additionally provided that the color (= phase) of the point is compared to the color of the closest ISO speed line. Thus, if the speed derived from the displacement and the speed derived from the color coincide with each other, a very high likelihood exists that there really occurs a movement with this speed. Further, the problem of ambiguities can be eliminated if the speed ambiguity intervals of the phase and of the pulse repetition frequency are different.
An alternative method for along-track interfermometry (ATI) consists in the subtraction of the results of the two antenna channels, also referred to as DPCA (Displaced Phase Center Antenna). Here, not the phase difference but the difference of the complex images of both antennae is generated. In the ideal case, the stationary background (clutter) is eliminated in the process, and the moving vehicles will be maintained as bright points. Also this image is suitably represented with superimposed road routes and lines of identical speeds.
The thus generated image is much better suited for interpretation than a s standard SAR image focused with constant parameters or even just a stack of images because, here, only one band along the road has to be evaluated in a single image and the visual evaluation is supported by the speed contours.
In Fig. 7, four examples of images obtained from data of the Shuttle Radar Topography Mission (SRTM) are schematically illustrated. In the conventional standard SAR image according to Fig. 7a, the vehicles and the road can be made out only with difficulties. The superimposed ISO speed lines representing multiples of 50 km/h are already helpful in the 1s interpretation of the SAR image, Still more easily surveyable is the variant according to Fig. 7b wherein only the relevant range has been focused, while also saving computational time. Fig. 7c illustrates the overall SAR
image with exclusively speed-adaptive focusing and with superimposed ISO
speed lines. Thus, the stationary clutter in the region of the road has an ambiguous appearance. For certain speed ranges outside of the clutter spectrum, the vehicles are now visualized much brighter. In Fig. 7d, the SAR image and the ISO speed lines are colored with respect to their interferometric phase. In this manner, it is also possible to eliminate ambiguities.
Claims (21)
1. A method for the processing and representing of ground images obtained by airplane- or space-based synthetic aperture radar sensor systems (SAR), characterized in that a known traffic route of a map, which is given by geographic coordinates and altitudes, is converted into azimuth/range coordinates of the SAR radar image, that a hypothetical radial speed (v r) of each image point of vehicles of potential relevance is determined from a distance of the image point to a traffic route in an azimuth direction and an appertaining vehicle image position is determined by azimuth projection onto the respective traffic route, that, from this hypothetical vehicle radial speed, a first focusing parameter .DELTA. fDC is derived in dependence on radar parameters, that from a hypothetical vehicle radial speed, an angle of incidence of a radar beam onto the surface of the earth and an angle between the respective traffic route and a flight path of the radar sensor, a hypothetical vehicle azimuth speed (v a) is derived and, therefrom, by inclusion of a flight path of a radar derived, and that the two focusing parameters .DELTA.fDC and .DELTA.FM derived from the hypothetical radial and azimuth speeds are plotted in a matrix and are used for exact adjustment of the SAR focusing to a moving object.
2. The method according to claim 1, characterized in that it is recorded in the map which regions do not need to be processed because a distance to the closest traffic route corresponds to an unrealistic speed of vehicles.
3, The method according to claim 1 or 2, characterized in that a road route is extracted from a digital road route database in the form of segments or a three-dimensional sequence of points {x, y, z}, that the segments and the sequence of points {(x, y, z), ... }, respectively, are transformed into an azimuth/range SAR radar coordinate system {(a s, r s,) ... }, that, from the segments and the sequence of points, respectively, there is interpolated a nearly continuous course for each pixel of the radar image and this road route is finally additionally superimposed to the radar image for visual evaluation, that, thereafter, for each pixel in the SAR range coordinate (r), a maximum range of displacement in the azimuth direction is determined on the basis of an assumed maximum vehicle speed V max, said maximum displacement range depending, corresponding to the equation on the angle of incidence .theta. and the local road angle .alpha., wherein V
SAR
denotes the airplane speed and R denotes the distance of the hypothetical vehicle image point from the radar sensor, and that, for each road route position {a s, r s}, the respective vehicle is imaged only into the range { [a s-.DELTA. a max, a s+.DELTA. a max] ,and then, for each possible image point {a, r} within the range {[a s-.DELTA. a max, a s ~ .DELTA. a max], r s}, the hypothetical radial speed and the hypothetical azimuth speed are computed, that, from these speed parameters, the two focusing film parameters .DELTA. fDC and .DELTA.FM are obtained which are used to adjust the SAR processor for the speed which is to be expected, and that this pair of focusing parameters is computed for each possibly relevant image point near the road route.
SAR
denotes the airplane speed and R denotes the distance of the hypothetical vehicle image point from the radar sensor, and that, for each road route position {a s, r s}, the respective vehicle is imaged only into the range { [a s-.DELTA. a max, a s+.DELTA. a max] ,and then, for each possible image point {a, r} within the range {[a s-.DELTA. a max, a s ~ .DELTA. a max], r s}, the hypothetical radial speed and the hypothetical azimuth speed are computed, that, from these speed parameters, the two focusing film parameters .DELTA. fDC and .DELTA.FM are obtained which are used to adjust the SAR processor for the speed which is to be expected, and that this pair of focusing parameters is computed for each possibly relevant image point near the road route.
4. The method according to claim 1, 2 or 3, characterized in that, for realizing subsequent SAR processing, there is used, according to a first variant, a special time range correlator which, for focusing each individual image point, correlates the SAR raw data using a two-dimensional correlation core, and that this correlation core is adapted for each image point with the aid of the two focusing parameters .DELTA.fDC and .DELTA.FM and, therefore, a mathematically exact and thus optimally focused movement-adaptive image is generated of the road route and of the vehicles driving on it.
5. The method according to claim 4, characterized in that, from potentially relevant speeds and positions, a control mask is computed and, to save time, the image is focused only for those areas which have been marked in a control mask.
6. The method according to any one of claims 1 to 3, characterized in that, for realizing the subsequent SAR processing, there are used, according to a second variant, standard SAR processors for discretizing the range between the extreme values of the first focusing parameter [A fDC min .DELTA.fDC max] into N intervals, interval boundaries being selected to the effect that processing errors caused by discretizing are tolerable, that average values of the intervals are orthogonally entered into a two-dimensional discretizing table, that, for each element of the discretizing table, which has a size Z = N x M, a belong into this discretizing interval, that the result resides in Z control masks which instruct the SAR processor as to which image portions have to be processed, that Z images covering all required Z
combinations of focusing parameters, are processed in Z standard SAR
processors which are connected in parallel or are arranged behind each other in the computer, and that, after Z partial images have now been obtained, these are assembled again into one image with the aid of the Z control masks, so that, as a result, an image of the road route and its surroundings is generated.
combinations of focusing parameters, are processed in Z standard SAR
processors which are connected in parallel or are arranged behind each other in the computer, and that, after Z partial images have now been obtained, these are assembled again into one image with the aid of the Z control masks, so that, as a result, an image of the road route and its surroundings is generated.
7. The method according to claim 6, characterized by slight modification of a standard SAR processor in such a manner that, by such a modified standard SAR processor, those processing steps which are independent from the two focusing parameters .DELTA.fDC and .DELTA.FM are carried out only once, and all subsequent processing steps are carried out Z times with adapted focusing parameters, so that the processor is to process for each image only the image points marked in a control mask, thus saving computational time.
8. The method according to any one of claims 1 to 3, characterized in that, for realizing the subsequent SAR processing, there is used, according to a third variant, a standard SAR processor for processing the scene with the aid of the average focusing parameters .DELTA.fDC and .DELTA. FM from the discretizing table, that, in this first step, focusing artifacts caused by the movement are tolerated and, additionally, a modification is performed which resides in that, prior to the focusing, a signal spectrum is replicated a plurality of times in the SAR
azimuth dimension to the effect that also moving objects are correctly processed by the processor with regard to their spectrum and their range migration, that the Doppler bandwidth of the SAR processor is correspondingly widely dimensioned for the following processing, so that the focused image thus includes the image of vehicles and clutter as well as their spectrally and spatially shifted versions, and that, thereafter, in a position-adaptive post-processing step, remaining movement unsharpness caused by the assumption of an average value of the second focusing parameter 6FM is corrected in the azimuth direction and the azimuth spectrum of the expected image is filtered out.
azimuth dimension to the effect that also moving objects are correctly processed by the processor with regard to their spectrum and their range migration, that the Doppler bandwidth of the SAR processor is correspondingly widely dimensioned for the following processing, so that the focused image thus includes the image of vehicles and clutter as well as their spectrally and spatially shifted versions, and that, thereafter, in a position-adaptive post-processing step, remaining movement unsharpness caused by the assumption of an average value of the second focusing parameter 6FM is corrected in the azimuth direction and the azimuth spectrum of the expected image is filtered out.
9. The method according to claim 8, characterized in that a control mask is used for processing only necessary image portions.
10. The method according to claim 8 or 9, characterized in that a scene with the average focusing parameters .DELTA.fDC and .DELTA.FM corresponds to a stationary scene.
11. The method according to any one of claims 8 to 10, characterized in that filtering is performed in the time domain.
12. The method according to any one of claims 8 to 10, characterized in that filtering is performed by fast convolution.
13. The method according to any one of claims 8 to 12, characterized by slight modification of a standard SAR processor in such a manner that, by such a modified standard SAR processor, those processing steps which are independent from the focusing parameters .DELTA.fDC and .DELTA.FM
are carried out only once, and all subsequent processing steps are carried out Z times with adapted focusing parameters, so that the processor is to process for each image only the image points marked in the control mask, thus saving computational time.
are carried out only once, and all subsequent processing steps are carried out Z times with adapted focusing parameters, so that the processor is to process for each image only the image points marked in the control mask, thus saving computational time.
14. The method according to any one of claims 1 to 13, characterized in that, for interferometric multi-antennae-systems, computation of the masks and of the speed-depedent parameters is carried out only once, and the actual SAR processing is performed separately for each antenna channel of the system.
15. The method according to any one of claims 1 to 14, characterized in that a novel representation of the image for the purposes of visual evaluation resides in that both the road route and the lines of the same speed are superimposed onto generated the SAR
image.
image.
16. The method according to claim 15, characterized in that the azimuth displacement for a constant speed V iso is computed, for each point of the road route in the range, on the basis of the equation these lines of identical speed being superimposed as ISO speed lines onto the SAR image like contour lines on a topographic map.
17. The method according to claim 15 and 16, characterized in that, in case of interferometric SAR with along-track interfermometry (ATI), said lines are plotted in colors corresponding to expected interferometric phase.
18. The method according to claim 17, characterized in that the SAR image is generated from two antenna channels and is colored corresponding to an interferometric phase difference between the two, channels, that the visual evaluation is performed in such a manner that bright points are assumed to represent vehicles and their speeds are estimated on the basis of the closest ISO speed lines, and that, in case of ATI processing, it is additionally provided that color, i.e.
the phase, of the point is compared to the color of the closest ISO
speed line, and that then, if the speed derived from displacement and the speed derived from color coincide with each other, the existence of a movement with this speed is assumed because there is a very high likelihood that there really occurs a movement with this speed.
the phase, of the point is compared to the color of the closest ISO
speed line, and that then, if the speed derived from displacement and the speed derived from color coincide with each other, the existence of a movement with this speed is assumed because there is a very high likelihood that there really occurs a movement with this speed.
19. The method according to claim 15 and 16, characterized in that, in case of multi-channel SAR including subtraction of the results of two antenna channels DPCA (Displaced Phase Center Antenna), a difference of complex images of two antennae is generated.
20. The method according to claim 19, characterized in that stationary background (clutter) is eliminated and the moving vehicles are maintained as bright points, and that the image is represented with superimposed road routes and lines of identical speeds.
21. The method according to any one of claims 1 to 20, characterized in that a defocusing resulting from an acceleration component in the radial direction relative to the SAR sensor antenna, which acceleration component has been caused by the vehicle following a curved route at constant speed, is compensated for by means of a modification residing in that, using a numerical mathematical derivation of the radial component v r of the speed, after a time period t a radial acceleration v r is computed according to the equation and that this radial acceleration v r results in a correction value of the frequency modulation rate, i.e. a correction value .DELTA.FM acc, for the second focusing parameter, and that the frequency modulation rate correction to be considered in focusing, i.e. the whole corrected second focusing parameter .DELTA.FM korr, is composed of the correction for the azimuth speed, i.e. the second focusing parameter .DELTA.FM, and the correction value of the frequency modulation rate, i.e. the computed correction value .DELTA.FM acc, according to the equation .DELTA.FM korr =
.DELTA.FM +
.DELTA.FM acc.
.DELTA.FM +
.DELTA.FM acc.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110389366A (en) * | 2019-08-05 | 2019-10-29 | 中国人民解放军军事科学院国防科技创新研究院 | A kind of naval target method for estimating based on multi-source SAR satellite |
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| US7739167B2 (en) | 1999-03-05 | 2010-06-15 | Era Systems Corporation | Automated management of airport revenues |
| US7889133B2 (en) | 1999-03-05 | 2011-02-15 | Itt Manufacturing Enterprises, Inc. | Multilateration enhancements for noise and operations management |
| US7782256B2 (en) | 1999-03-05 | 2010-08-24 | Era Systems Corporation | Enhanced passive coherent location techniques to track and identify UAVs, UCAVs, MAVs, and other objects |
| US7908077B2 (en) | 2003-06-10 | 2011-03-15 | Itt Manufacturing Enterprises, Inc. | Land use compatibility planning software |
| US7777675B2 (en) | 1999-03-05 | 2010-08-17 | Era Systems Corporation | Deployable passive broadband aircraft tracking |
| US7570214B2 (en) | 1999-03-05 | 2009-08-04 | Era Systems, Inc. | Method and apparatus for ADS-B validation, active and passive multilateration, and elliptical surviellance |
| US8203486B1 (en) | 1999-03-05 | 2012-06-19 | Omnipol A.S. | Transmitter independent techniques to extend the performance of passive coherent location |
| US8446321B2 (en) | 1999-03-05 | 2013-05-21 | Omnipol A.S. | Deployable intelligence and tracking system for homeland security and search and rescue |
| US7667647B2 (en) | 1999-03-05 | 2010-02-23 | Era Systems Corporation | Extension of aircraft tracking and positive identification from movement areas into non-movement areas |
| US7965227B2 (en) | 2006-05-08 | 2011-06-21 | Era Systems, Inc. | Aircraft tracking using low cost tagging as a discriminator |
| DE102009007704A1 (en) | 2009-02-05 | 2010-08-12 | Daimler Ag | Method for detecting probable lane of passenger car, involve compensating displacement of vehicle, such that detection area of radar system is virtually increased, while considering radar images during generation of total radar image |
| DE102009013768A1 (en) * | 2009-03-18 | 2010-10-14 | Eads Deutschland Gmbh | Method and device for determining aspect angles |
| CN103377558A (en) * | 2012-04-26 | 2013-10-30 | 鸿富锦精密工业（深圳）有限公司 | System and method for managing and controlling traffic flow |
| CN108305274B (en) * | 2018-03-08 | 2021-11-23 | 中国民航大学 | PolSAR image multi-feature fusion aircraft target detection method |
| CN108549063B (en) * | 2018-06-29 | 2021-11-26 | 北京航空航天大学 | Method for quickly estimating track speed of moving target in satellite-borne synthetic aperture radar image |
| KR102653404B1 (en) * | 2020-05-08 | 2024-04-02 | 주식회사 에이치엘클레무브 | control device for vehicle and control method thereof |
| DE102020207879A1 (en) * | 2020-06-25 | 2021-12-30 | Robert Bosch Gesellschaft mit beschränkter Haftung | Method for operating a radar sensor in a motor vehicle |
| CN113960599B (en) * | 2021-09-17 | 2024-05-31 | 北京工商大学 | Scanning mode SAR imaging refocusing method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| DE4423899C1 (en) * | 1994-07-08 | 1995-11-02 | Deutsche Forsch Luft Raumfahrt | Method for the detection, localization and speed determination of moving targets from raw radar data of a coherent, single or multi-channel imaging system carried by a carrier |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110389366A (en) * | 2019-08-05 | 2019-10-29 | 中国人民解放军军事科学院国防科技创新研究院 | A kind of naval target method for estimating based on multi-source SAR satellite |
| CN110389366B (en) * | 2019-08-05 | 2021-03-30 | 中国人民解放军军事科学院国防科技创新研究院 | Maritime target motion estimation method based on multi-source SAR satellite |
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| ITSV20070006A1 (en) | 2007-08-25 |
| CA2579898A1 (en) | 2007-08-24 |
| DE102006009121A1 (en) | 2007-08-30 |
| DE102006009121B4 (en) | 2012-05-31 |
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