CN204406211U - The aerial recognition system of Gobi desert area road - Google Patents
The aerial recognition system of Gobi desert area road Download PDFInfo
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- CN204406211U CN204406211U CN201520136578.XU CN201520136578U CN204406211U CN 204406211 U CN204406211 U CN 204406211U CN 201520136578 U CN201520136578 U CN 201520136578U CN 204406211 U CN204406211 U CN 204406211U
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Abstract
The utility model relates to the aerial recognition system of a kind of Gobi desert area road, described aerial recognition system is mounted on unmanned plane, comprise the Big Dipper steady arm, highly sensing equipment, aerial camera, road Identification equipment and digital signal processor DSP, described DSP and described the Big Dipper steady arm, described highly sensing equipment, described aerial camera is connected respectively with described road Identification equipment, what the real time positioning data exported based on described the Big Dipper steady arm and described highly sensing equipment exported highly determine whether in real time starts described aerial camera and described road Identification equipment to realize identifying the road in region, described Gobi desert in the air.By the utility model, road Identification fast, accurately can being realized to the region, Gobi desert of complex landform, providing more effective reference information for travelling at the vehicle in region, Gobi desert.
Description
Technical field
The utility model relates to road positioning field, particularly relates to the aerial recognition system of a kind of Gobi desert area road.
Background technology
Gobi desert is a type of desert, i.e. the desert of mild, the large stretch of gravel of covered ground of relief, from Mongol.Ground is blown off by wind because of spun yarn, and remaining gravel blanket, thus have the difference of gravel matter desert and stone matter desert, Mongol claims gravel matter desert to be Gobi desert.In region, Gobi desert, be full of sand and stone, lack of water on ground, plant is rare.
Draw in the daily road drawing of department at road, comparatively simply location and the route drafting of urban road, because urban road has road and the obvious characteristic feature of urban background edge boundary, therefore satellite remote sensing is used can effectively to extract related roads information, and the road of Gobi Region is drawn, due to a varied topography, the edge boundary of road and Gobi desert background is fuzzy, some roads Bu Shi road administration department builds, but the dirt road that local resident renovates, or even the irregular route that vehicular traffic rolls for a long time and formed, at this moment the mode re-using satellite remote sensing carries out road survey, its precision can not meet requirement, and go to carry out road survey by the means of on-site land survey, its real-time and efficiency are too poor again.
Therefore, need a kind of technical scheme of new Gobi desert area road identification, for the region, Gobi desert of complex landform, specific recognition mechanism and Identification platform can be formulated targetedly, thus the measurement completed quickly and accurately Gobi desert area road and location.
Summary of the invention
In order to solve the problem, the utility model provides the aerial recognition system of a kind of Gobi desert area road, in Identification platform, Identification platform is built based on unmanned plane, utilize flexible, the comprehensive feature of unmanned plane, improve identification high efficiency and the real-time of the utility model recognition system, simultaneously, in order to accurately obtain the relevant information of Gobi desert area road, recognition mechanism customizes the processing sequence of each image processing equipment and contents processing, to improve the accuracy of identification of the utility model recognition system.
According to one side of the present utility model, provide the aerial recognition system of a kind of Gobi desert area road, described aerial recognition system is mounted on unmanned plane, comprise the Big Dipper steady arm, highly sensing equipment, aerial camera, road Identification equipment and digital signal processor DSP, described DSP and described the Big Dipper steady arm, described highly sensing equipment, described aerial camera is connected respectively with described road Identification equipment, what the real time positioning data exported based on described the Big Dipper steady arm and described highly sensing equipment exported highly determine whether in real time starts described aerial camera and described road Identification equipment to realize identifying the road in region, described Gobi desert in the air.
More specifically, in the aerial recognition system of described Gobi desert area road, also comprising: unmanned plane driving arrangement, to fly to position directly over region, described Gobi desert for driving described unmanned plane under the control of described DSP, static memory, for prestoring Gobi desert area road R channel range, Gobi desert area road G channel range, Gobi desert area road channel B scope, described Gobi desert area road R channel range, described Gobi desert area road G channel range and described Gobi desert area road channel B scope are used for being separated with RGB image background by the Gobi desert area road in RGB image, also for prestoring preset height scope, preset pressure elevation weight and default ultrasonic height weight, transceiver, draw platform with the Gobi desert area road of far-end and set up two-way wireless communication link, draw the flight steering order of platform transmission for receiving described Gobi desert area road, described flight steering order comprises the object the Big Dipper data and object shooting height that directly over region, described Gobi desert, position is corresponding, described the Big Dipper steady arm connects the Big Dipper Navsat, for receiving the real time positioning data of unmanned plane position, described highly sensing equipment is connected with described static memory, comprises pressure-altitude sensor, ultrasonic height sensors and master controller, described pressure-altitude sensor is used for according to the air pressure change near unmanned plane, detects the real-time barometer altitude of unmanned plane position, described ultrasonic height sensors comprises ultrasound wave emitter, ultrasonic receiver and single-chip microcomputer, described single-chip microcomputer is connected respectively with described ultrasound wave emitter and described ultrasonic receiver, described ultrasound wave emitter launches ultrasound wave earthward, described ultrasonic receiver receives the ultrasound wave of ground return, and described single-chip microcomputer calculates the real-time ultrasound wave height of unmanned plane according to the launch time of described ultrasound wave emitter, the time of reception of described ultrasonic receiver and ultrasonic propagation velocity, described master controller is connected respectively with described pressure-altitude sensor, described ultrasonic height sensors and described static memory, when the difference of described real-time barometer altitude and described real-time ultrasound wave height is in described preset height scope, calculate based on described preset pressure elevation weight, described default ultrasonic height weight, described real-time barometer altitude and described real-time ultrasound wave height and export described real-time height, when the difference of described real-time barometer altitude and described real-time ultrasound wave height is not in described preset height scope, export height detection failure signal, described aerial camera is linear array digital aviation video camera, comprises undercarriage having shock absorption function, front cover glass, camera lens, filter and image-forming electron unit, for taking region, described Gobi desert to obtain Gobi desert area image, described road Identification equipment is connected respectively with described static memory and described aerial camera, comprise color space conversion subset, histogram equalization subset, separation of images subset, wavelet filtering subset and least square fitting subset, described color space conversion subset is connected with described aerial camera, for performing rgb color space conversion to described Gobi desert area image, obtain region, Gobi desert RGB image, described histogram equalization subset and described color space are changed subset and are connected, and perform based on the image enhancement processing of histogram equalization to region, described Gobi desert RGB image, to obtain the enhancing image that road and background contrasts strengthen, described separation of images subset is connected respectively with described static memory and described histogram equalization subset, calculate the R channel value of each pixel in described enhancing image, G channel value and channel B value, when the R channel value of a certain pixel in the area road R channel range of described Gobi desert, G channel value in the area road G channel range of described Gobi desert and channel B value within the scope of the area road channel B of described Gobi desert time, be defined as road pixel, by road pixel combinations all in described enhancing image to form road subimage, described wavelet filtering subset is connected with described separation of images subset, performs filtering process, to obtain the filtering road subimage of filtering noise pixel based on Haar wavelet transform wave filter to described road subimage, described least square fitting subset is connected with described wavelet filtering subset, perform process of fitting treatment to determine road curve based on least square fitting algorithm to described filtering road subimage, described road curve is and the square distance of all pixels in described filtering road subimage and minimum curve, described DSP and described unmanned plane driving arrangement, described transceiver, described the Big Dipper steady arm, described highly sensing equipment, described aerial camera is connected respectively with described road Identification equipment, receive the flight steering order that described transceiver forwards, described flight steering order is resolved to obtain the object the Big Dipper data and object shooting height that directly over region, described Gobi desert, position is corresponding, control described unmanned plane driving arrangement to fly to position directly over region, described Gobi desert to drive described unmanned plane, described real-time height to mate with described object shooting height and described real time positioning data and described object the Big Dipper Data Matching time, enter road Identification pattern, when described real-time height does not mate with described object shooting height or described real time positioning data does not mate with described object the Big Dipper data, enter region, Gobi desert searching modes, when receiving described height detection failure signal, enter automatic fault selftesting pattern, wherein, described DSP is in described road Identification pattern, start described aerial camera and described road Identification equipment, receive described Gobi desert area image and described road curve, determine the relative position of described road curve in the area image of described Gobi desert, based on described relative position, described real time positioning data and the described locating information highly determining described road curve in real time, the locating information of described road curve comprises the locating information of the locating information of the starting point of described road curve and the terminal of described road curve, described transceiver receives the locating information of described road curve and described road curve, and the locating information of described road curve and described road curve is wirelessly sent to described Gobi desert area road drafting platform.
More specifically, in the aerial recognition system of described Gobi desert area road, also comprise: power-supply unit, be connected with described DSP, under the control of described DSP for each consuming parts in described aerial recognition system provides electric power supply.
More specifically, in the aerial recognition system of described Gobi desert area road: described transceiver comprises wireless receiver and radio transmitters.
More specifically, in the aerial recognition system of described Gobi desert area road: described DSP, in the searching modes of region, described Gobi desert, closes described aerial camera and described road Identification equipment.
More specifically, in the aerial recognition system of described Gobi desert area road: described DSP is in described automatic fault selftesting pattern, fault self-checking is performed to described aerial recognition system, and the failure code corresponding to self-inspection fault type is out transmitted to described Gobi desert area road by described transceiver draws platform.
Accompanying drawing explanation
Below with reference to accompanying drawing, embodiment of the present utility model is described, wherein:
Fig. 1 is the block diagram of the aerial recognition system of Gobi desert area road according to the utility model embodiment.
Fig. 2 is the block diagram of the highly sensing equipment of the aerial recognition system of Gobi desert area road according to the utility model embodiment.
Embodiment
Below with reference to accompanying drawings the embodiment of the aerial recognition system of Gobi desert of the present utility model area road is described in detail.
On the earth, the road Identification of regional is significant, not only can provide navigation information for car and crowd, and can succour for natural disaster, emergency relief etc. provides valuable reference information, improves the efficiency of rescue and relief.But dissimilar region, the difficulty of road Identification is different.Wherein, the most difficult region, Gobi desert no more than landforms complexity.
Most area, Gobi desert is not desert but naked rock, refer to ground almost by rough sand, gravel cover, the desert belt of plant rareness.Scientist thinks, since 2000000 years, particularly since hundreds of thousands year, because physical features constantly rises, dry climate district constantly expands, the rock mass that the sandstone that terrain surface deposits, silty and glutenite etc. relatively loosen, under the sun and wind action, constantly by weathering and erosion, becomes a large amount of detrital material.The detrital material that these sizes mix gets off from disintegration mountain, starts to pile up at the foot of the hill.Under the effect of flood, be flushed to piedmont belt far away, form large-area flood plain.Whenever dry season, it is aerial that the fine sand in the detrital material under large wind action on flood plain and dust are blown to sky, and wherein dust is blown to the area outside a thousand li, defines loess plateau; Near those fine sands are then carried to by wind, form desert.The gravel that particle diameter is larger, be then left on original place, just defines Gobi desert landforms of today.
Gobi desert is coarse sand, the clod cover desert landform on hard stratum.By origin cause of formation conglomerate re servoir can be divided into weathering, water become with eolian three kinds.It forms main cause is because flood alluviation forms.Work as Flooding, particularly during the Flooding of mountain area, due to weakening gradually of flood energy of coming out of retirement and taking up an official post, impact area at flood and form following morphologic characteristics: the rock deposit of bulk is from the nearest mountain pass place of massif, and rock diminishes successively outside mountain; What occur subsequently is exactly the rock of fist size to finger size.Due to Exposure to Sunlight year in year out, drench with rain and the degrading of strong wind, corner angle are rounding all gradually, becomes our said stone (formal name used at school is in gravel).Like this, Gobi desert also just defines.Those more tiny sand and mud then by alluviation, floating farther, define the nefud of farther place.
Region, Gobi desert is generally in remote area, lessly there is the standard road that road administration department builds, it is more the dirt road that local resident renovates, or even the irregular route that vehicular traffic rolls for a long time and formed, due to a varied topography, the edge boundary of road and Gobi desert background is fuzzy, and conventional satellite remote sensing mode accurately cannot identify road, and the means of manual site's exploration are too original.
The utility model has built the aerial recognition system of a kind of Gobi desert area road, with unmanned plane flexibly for measuring table, based on a set of road Identification equipment be made up of multiple image procossing subset of Gobi desert special geomorphology customization, realize effective, the road Identification fast and accurately to region, selected Gobi desert, draw department for relevant road and more valuable road data is provided.
Fig. 1 is the block diagram of the aerial recognition system of Gobi desert area road according to the utility model embodiment, described aerial recognition system is mounted in unmanned plane, comprise the Big Dipper steady arm 1, highly sensing equipment 2, aerial camera 3, road Identification equipment 4 and digital signal processor DSP 5, described DSP 5 and described the Big Dipper steady arm 1, described highly sensing equipment 2, described aerial camera 3 is connected respectively with described road Identification equipment 4, what the real time positioning data exported based on described the Big Dipper steady arm 1 and described highly sensing equipment 2 exported highly determine whether in real time starts described aerial camera 3 and described road Identification equipment 4 to realize identifying the road in region, described Gobi desert in the air.
Then, continue to be further detailed the concrete structure of the aerial recognition system of Gobi desert of the present utility model area road.
Described aerial recognition system also comprises: unmanned plane driving arrangement, to fly to position directly over region, described Gobi desert for driving described unmanned plane under the control of described DSP 5.
Described aerial recognition system also comprises: static memory, for prestoring Gobi desert area road R channel range, Gobi desert area road G channel range, Gobi desert area road channel B scope, described Gobi desert area road R channel range, described Gobi desert area road G channel range and described Gobi desert area road channel B scope are used for being separated with RGB image background by the Gobi desert area road in RGB image, also for prestoring preset height scope, preset pressure elevation weight and default ultrasonic height weight.
Described aerial recognition system also comprises: transceiver, draw platform with the Gobi desert area road of far-end and set up two-way wireless communication link, draw the flight steering order of platform transmission for receiving described Gobi desert area road, described flight steering order comprises the object the Big Dipper data and object shooting height that directly over region, described Gobi desert, position is corresponding.
Described the Big Dipper steady arm 1 connects the Big Dipper Navsat, for receiving the real time positioning data of unmanned plane position.
As shown in Figure 2, described highly sensing equipment 2 is connected with described static memory, comprises pressure-altitude sensor 21, ultrasonic height sensors 22 and master controller 23.
Described pressure-altitude sensor 21, for according to the air pressure change near unmanned plane, detects the real-time barometer altitude of unmanned plane position.
Described ultrasonic height sensors 22 comprises ultrasound wave emitter, ultrasonic receiver and single-chip microcomputer, described single-chip microcomputer is connected respectively with described ultrasound wave emitter and described ultrasonic receiver, described ultrasound wave emitter launches ultrasound wave earthward, described ultrasonic receiver receives the ultrasound wave of ground return, and described single-chip microcomputer calculates the real-time ultrasound wave height of unmanned plane according to the launch time of described ultrasound wave emitter, the time of reception of described ultrasonic receiver and ultrasonic propagation velocity.
Described master controller 23 is connected respectively with described pressure-altitude sensor 21, described ultrasonic height sensors 22 and described static memory, when the difference of described real-time barometer altitude and described real-time ultrasound wave height is in described preset height scope, calculate based on described preset pressure elevation weight, described default ultrasonic height weight, described real-time barometer altitude and described real-time ultrasound wave height and export described real-time height, when the difference of described real-time barometer altitude and described real-time ultrasound wave height is not in described preset height scope, export height detection failure signal.
Described aerial camera 3 is linear array digital aviation video camera, comprises undercarriage having shock absorption function, front cover glass, camera lens, filter and image-forming electron unit, for taking region, described Gobi desert to obtain Gobi desert area image.
Described road Identification equipment 4 is connected respectively with described static memory and described aerial camera 3, and described road Identification equipment 4 comprises color space conversion subset, histogram equalization subset, separation of images subset, wavelet filtering subset and least square fitting subset.
Described color space conversion subset is connected with described aerial camera 3, for performing rgb color space conversion to described Gobi desert area image, obtains region, Gobi desert RGB image.
Described histogram equalization subset and described color space are changed subset and are connected, and perform based on the image enhancement processing of histogram equalization to region, described Gobi desert RGB image, to obtain the enhancing image that road and background contrasts strengthen.
Described separation of images subset is connected respectively with described static memory and described histogram equalization subset, calculate the R channel value of each pixel in described enhancing image, G channel value and channel B value, when the R channel value of a certain pixel in the area road R channel range of described Gobi desert, G channel value in the area road G channel range of described Gobi desert and channel B value within the scope of the area road channel B of described Gobi desert time, be defined as road pixel, by road pixel combinations all in described enhancing image to form road subimage.
Described wavelet filtering subset is connected with described separation of images subset, performs filtering process, to obtain the filtering road subimage of filtering noise pixel based on Haar wavelet transform wave filter to described road subimage.
Described least square fitting subset is connected with described wavelet filtering subset, perform process of fitting treatment to determine road curve based on least square fitting algorithm to described filtering road subimage, described road curve is and the square distance of all pixels in described filtering road subimage and minimum curve.
Described DSP 5 and described unmanned plane driving arrangement, described transceiver, described the Big Dipper steady arm 1, described highly sensing equipment 2, described aerial camera 3 is connected respectively with described road Identification equipment 4, receive the flight steering order that described transceiver forwards, described flight steering order is resolved to obtain the object the Big Dipper data and object shooting height that directly over region, described Gobi desert, position is corresponding, control described unmanned plane driving arrangement to fly to position directly over region, described Gobi desert to drive described unmanned plane, described real-time height to mate with described object shooting height and described real time positioning data and described object the Big Dipper Data Matching time, enter road Identification pattern, when described real-time height does not mate with described object shooting height or described real time positioning data does not mate with described object the Big Dipper data, enter region, Gobi desert searching modes, when receiving described height detection failure signal, enter automatic fault selftesting pattern.
Wherein, described DSP 5 is in described road Identification pattern, start described aerial camera 3 and described road Identification equipment 4, receive described Gobi desert area image and described road curve, determine the relative position of described road curve in the area image of described Gobi desert, based on described relative position, described real time positioning data and the described locating information highly determining described road curve in real time, the locating information of described road curve comprises the locating information of the locating information of the starting point of described road curve and the terminal of described road curve; Described transceiver receives the locating information of described road curve and described road curve, and the locating information of described road curve and described road curve is wirelessly sent to described Gobi desert area road drafting platform.
Wherein, the described Gobi desert aerial recognition system of area road can also comprise power-supply unit, is connected with described DSP 5, under the control of described DSP 5 for each consuming parts in described aerial recognition system provides electric power supply; Alternatively, described transceiver comprises wireless receiver and radio transmitters, described DSP 5 is in the searching modes of region, described Gobi desert, close described aerial camera 3 and described road Identification equipment 4, described DSP 5 is in described automatic fault selftesting pattern, fault self-checking is performed to described aerial recognition system, and the failure code corresponding to self-inspection fault type is out transmitted to described Gobi desert area road by described transceiver draws platform; And described aerial camera 3 is high resolving power aerial camera, its resolution is 1920 × 1080 even higher, and described master controller 23 can type selecting be also AT89C51 system.
In addition, single-chip microcomputer (Microcontrollers) is a kind of integrated circuit (IC) chip, adopt very large scale integration technology to be integrated into the little and perfect microcomputer system of that one piece of silicon chip is formed, in industrial control field widespread use having the central processor CPU of data-handling capacity, random access memory ram, read only memory ROM, multiple I/O mouth and the function such as interrupt system, timer/counter (may also comprise the circuit such as display driver circuit, pulse-width modulation circuit, analog multiplexer, A/D converter).
From the eighties in last century, by 4 at that time, 8 single-chip microcomputers, develop into the high-speed microprocessor of present 300M.The use field of single-chip microcomputer is very extensive, as intelligent instrument, in real time industry control, communication apparatus, navigational system, household electrical appliance etc.Various product, once use single-chip microcomputer, just can play the effect making the updating and upgrading of a product, titled with adjective " intelligent " before name of product of being everlasting, as Intelligent Washing Machine etc.
Single-chip microcomputer is born in 1971, and experienced by SCM, MCU, SoC tri-megastage, early stage SCM single-chip microcomputer is all 8 or 4.Be the most successfully wherein 8051 of INTEL, on 8051, after this developed MCS51 Series MCU system.Single Chip Microcomputer (SCM) system based on this system is also widely using up to now.Along with the raising that industrial control field requires, start to have occurred 16 single-chip microcomputers, but because undesirable not the obtaining of cost performance is applied very widely.Along with consumption electronic product great development after the nineties, singlechip technology obtains huge raising.Along with the widespread use of INTEL i960 series particularly ARM series afterwards, 32 single-chip microcomputers replace rapidly the high end status of 16 single-chip microcomputers, and enter mainstream market.And the performance of traditional 8 single-chip microcomputers have also been obtained raising at full speed, processing power improves hundreds of times compared with the eighties.32 high-end Soc single-chip microcomputer dominant frequency are more than 300MHz, and performance directly chases after the application specific processor of the mid-90, and common model factory price drops to 1 dollar, and the model of most significant end also only has 10 dollars.
No longer only exploitation and the use under bare machine environment of Single Chip Microcomputer (SCM) system in the present age, embedded OS special is in a large number widely used on the single-chip microcomputer of complete series.And even can directly use special Windows and (SuSE) Linux OS at the high-end single-chip microcomputer as palm PC and mobile phone core processing.
AT89C51 is a kind of low-voltage, high-performance CMOS 8-bit microprocessor of band 4K byte FLASH memory (FPEROM-FlashProgrammable and Erasable Read Only Memory), also with 2K byte Flash-Programmable erasable read-only memory.The erasable read-only memory of single-chip microcomputer can wipe 1000 times repeatedly.This device adopts ATMEL high density nonvolatile memory manufacturing technology to manufacture, with the MCS-51 instruction set of industrial standard and output pin mutually compatible.Owing to being combined in one single chip by multi-functional 8 bit CPUs and flash memory, the AT89C51 of ATMEL is a kind of efficient microcontroller, and AT89C2051 is its a kind of compact version.AT89C51 single-chip microcomputer is that a lot of embedded control system provides the high and inexpensive scheme of a kind of dirigibility.
Adopt the aerial recognition system of Gobi desert of the present utility model area road, for existing satellite remote sensing recognition method measuring error is comparatively large and manual site's recognition method measurement efficiency is low and the technical matters of poor real, by adopting unmanned aerial vehicle platform, the more image processing equipments targetedly of introducing, the more efficient image processing procedure of planning flexibly, form a set of Gobi desert area road recognition system that simultaneously can meet high precision, high-level efficiency and high real-time.
Be understandable that, although the utility model with preferred embodiment disclose as above, but above-described embodiment and be not used to limit the utility model.For any those of ordinary skill in the art, do not departing under technical solutions of the utility model ambit, the technology contents of above-mentioned announcement all can be utilized to make many possible variations and modification to technical solutions of the utility model, or be revised as the Equivalent embodiments of equivalent variations.Therefore, every content not departing from technical solutions of the utility model, according to technical spirit of the present utility model to any simple modification made for any of the above embodiments, equivalent variations and modification, all still belongs in the scope of technical solutions of the utility model protection.
Claims (6)
1. the aerial recognition system of Gobi desert area road, described aerial recognition system is mounted on unmanned plane, it is characterized in that, described aerial recognition system comprises the Big Dipper steady arm, highly sensing equipment, aerial camera, road Identification equipment and digital signal processor DSP, described DSP and described the Big Dipper steady arm, described highly sensing equipment, described aerial camera is connected respectively with described road Identification equipment, what the real time positioning data exported based on described the Big Dipper steady arm and described highly sensing equipment exported highly determine whether in real time starts described aerial camera and described road Identification equipment to realize identifying the road in region, described Gobi desert in the air.
2. area road aerial recognition system in Gobi desert as claimed in claim 1, it is characterized in that, described aerial recognition system also comprises:
Unmanned plane driving arrangement, to fly to position directly over region, described Gobi desert for driving described unmanned plane under the control of described DSP;
Static memory, for prestoring Gobi desert area road R channel range, Gobi desert area road G channel range, Gobi desert area road channel B scope, described Gobi desert area road R channel range, described Gobi desert area road G channel range and described Gobi desert area road channel B scope are used for being separated with RGB image background by the Gobi desert area road in RGB image, also for prestoring preset height scope, preset pressure elevation weight and default ultrasonic height weight;
Transceiver, draw platform with the Gobi desert area road of far-end and set up two-way wireless communication link, draw the flight steering order of platform transmission for receiving described Gobi desert area road, described flight steering order comprises the object the Big Dipper data and object shooting height that directly over region, described Gobi desert, position is corresponding;
Described the Big Dipper steady arm connects the Big Dipper Navsat, for receiving the real time positioning data of unmanned plane position;
Described highly sensing equipment is connected with described static memory, comprises pressure-altitude sensor, ultrasonic height sensors and master controller; Described pressure-altitude sensor is used for according to the air pressure change near unmanned plane, detects the real-time barometer altitude of unmanned plane position; Described ultrasonic height sensors comprises ultrasound wave emitter, ultrasonic receiver and single-chip microcomputer, described single-chip microcomputer is connected respectively with described ultrasound wave emitter and described ultrasonic receiver, described ultrasound wave emitter launches ultrasound wave earthward, described ultrasonic receiver receives the ultrasound wave of ground return, and described single-chip microcomputer calculates the real-time ultrasound wave height of unmanned plane according to the launch time of described ultrasound wave emitter, the time of reception of described ultrasonic receiver and ultrasonic propagation velocity; Described master controller is connected respectively with described pressure-altitude sensor, described ultrasonic height sensors and described static memory, when the difference of described real-time barometer altitude and described real-time ultrasound wave height is in described preset height scope, calculate based on described preset pressure elevation weight, described default ultrasonic height weight, described real-time barometer altitude and described real-time ultrasound wave height and export described real-time height, when the difference of described real-time barometer altitude and described real-time ultrasound wave height is not in described preset height scope, export height detection failure signal;
Described aerial camera is linear array digital aviation video camera, comprises undercarriage having shock absorption function, front cover glass, camera lens, filter and image-forming electron unit, for taking region, described Gobi desert to obtain Gobi desert area image;
Described road Identification equipment is connected respectively with described static memory and described aerial camera, comprise color space conversion subset, histogram equalization subset, separation of images subset, wavelet filtering subset and least square fitting subset, described color space conversion subset is connected with described aerial camera, for performing rgb color space conversion to described Gobi desert area image, obtain region, Gobi desert RGB image; Described histogram equalization subset and described color space are changed subset and are connected, and perform based on the image enhancement processing of histogram equalization to region, described Gobi desert RGB image, to obtain the enhancing image that road and background contrasts strengthen; Described separation of images subset is connected respectively with described static memory and described histogram equalization subset, calculate the R channel value of each pixel in described enhancing image, G channel value and channel B value, when the R channel value of a certain pixel in the area road R channel range of described Gobi desert, G channel value in the area road G channel range of described Gobi desert and channel B value within the scope of the area road channel B of described Gobi desert time, be defined as road pixel, by road pixel combinations all in described enhancing image to form road subimage; Described wavelet filtering subset is connected with described separation of images subset, performs filtering process, to obtain the filtering road subimage of filtering noise pixel based on Haar wavelet transform wave filter to described road subimage; Described least square fitting subset is connected with described wavelet filtering subset, perform process of fitting treatment to determine road curve based on least square fitting algorithm to described filtering road subimage, described road curve is and the square distance of all pixels in described filtering road subimage and minimum curve;
Described DSP and described unmanned plane driving arrangement, described transceiver, described the Big Dipper steady arm, described highly sensing equipment, described aerial camera is connected respectively with described road Identification equipment, receive the flight steering order that described transceiver forwards, described flight steering order is resolved to obtain the object the Big Dipper data and object shooting height that directly over region, described Gobi desert, position is corresponding, control described unmanned plane driving arrangement to fly to position directly over region, described Gobi desert to drive described unmanned plane, described real-time height to mate with described object shooting height and described real time positioning data and described object the Big Dipper Data Matching time, enter road Identification pattern, when described real-time height does not mate with described object shooting height or described real time positioning data does not mate with described object the Big Dipper data, enter region, Gobi desert searching modes, when receiving described height detection failure signal, enter automatic fault selftesting pattern,
Wherein, described DSP is in described road Identification pattern, start described aerial camera and described road Identification equipment, receive described Gobi desert area image and described road curve, determine the relative position of described road curve in the area image of described Gobi desert, based on described relative position, described real time positioning data and the described locating information highly determining described road curve in real time, the locating information of described road curve comprises the locating information of the locating information of the starting point of described road curve and the terminal of described road curve;
Wherein, described transceiver receives the locating information of described road curve and described road curve, and the locating information of described road curve and described road curve is wirelessly sent to described Gobi desert area road drafting platform.
3. area road aerial recognition system in Gobi desert as claimed in claim 2, it is characterized in that, described aerial recognition system also comprises:
Power-supply unit, is connected with described DSP, under the control of described DSP for each consuming parts in described aerial recognition system provides electric power supply.
4. area road aerial recognition system in Gobi desert as claimed in claim 2, is characterized in that:
Described transceiver comprises wireless receiver and radio transmitters.
5. area road aerial recognition system in Gobi desert as claimed in claim 2, is characterized in that:
Described DSP, in the searching modes of region, described Gobi desert, closes described aerial camera and described road Identification equipment.
6. area road aerial recognition system in Gobi desert as claimed in claim 2, is characterized in that:
Described DSP, in described automatic fault selftesting pattern, performs fault self-checking to described aerial recognition system, and the failure code corresponding to self-inspection fault type is out transmitted to described Gobi desert area road by described transceiver draws platform.
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| CN201520136578.XU Withdrawn - After Issue CN204406211U (en) | 2015-03-10 | 2015-03-10 | The aerial recognition system of Gobi desert area road |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104699112A (en) * | 2015-03-10 | 2015-06-10 | 无锡桑尼安科技有限公司 | Aerial identification system of roads in Gobi district |
| CN108351620A (en) * | 2015-09-16 | 2018-07-31 | 深圳市大疆创新科技有限公司 | Method and apparatus for operating mobile platform |
-
2015
- 2015-03-10 CN CN201520136578.XU patent/CN204406211U/en not_active Withdrawn - After Issue
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104699112A (en) * | 2015-03-10 | 2015-06-10 | 无锡桑尼安科技有限公司 | Aerial identification system of roads in Gobi district |
| CN104699112B (en) * | 2015-03-10 | 2016-09-14 | 南通市广益机电有限责任公司 | Gobi desert area road identifies system in the air |
| CN108351620A (en) * | 2015-09-16 | 2018-07-31 | 深圳市大疆创新科技有限公司 | Method and apparatus for operating mobile platform |
| US11320793B2 (en) | 2015-09-16 | 2022-05-03 | SZ DJI Technology Co., Ltd. | Method and apparatus for operating mobile platform |
| US11669054B2 (en) | 2015-09-16 | 2023-06-06 | SZ DJI Technology Co., Ltd. | Method and apparatus for operating mobile platform |
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