CN109471067B - High-precision wheel type mobile target positioning system and method based on wireless signals - Google Patents
High-precision wheel type mobile target positioning system and method based on wireless signals Download PDFInfo
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- CN109471067B CN109471067B CN201811264689.3A CN201811264689A CN109471067B CN 109471067 B CN109471067 B CN 109471067B CN 201811264689 A CN201811264689 A CN 201811264689A CN 109471067 B CN109471067 B CN 109471067B
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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
- G01S13/904—SAR modes
- G01S13/9082—Rotating SAR [ROSAR]
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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
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/0205—Details
- G01S5/021—Calibration, monitoring or correction
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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
- G01S13/9029—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
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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
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/06—Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements
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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
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/10—Position of receiver fixed by co-ordinating a plurality of position lines defined by path-difference measurements, e.g. omega or decca systems
Abstract
A wheeled mobile target high-precision positioning system and method based on wireless signals comprises the following steps: the Wi-Fi positioning system comprises a signal state information acquisition module for receiving Wi-Fi signals, a sensing calculation module for inertial sensing and executing a positioning algorithm, and power modules connected with the sensing calculation module and the sensing calculation module, wherein: the signal state information acquisition module receives wireless channel state information and transmits the information to the sensing calculation module, and the sensing calculation module takes the received wireless channel information as the input of a positioning algorithm and obtains the current position of the target through calculation. According to the invention, the antenna rotating together with the wheel is used, the motion track of the antenna is described by using the inertial sensor, a large-scale antenna array is constructed, the arrival time and the arrival angle of Wi-Fi signals are calculated, and then the high-precision positioning of the wheeled moving target is realized.
Description
Technical Field
The invention relates to a technology in the field of wireless signal positioning, in particular to a wheel type mobile target high-precision positioning system and method based on Wi-Fi, wherein the positioning precision can reach within 1 meter under three environments of indoor, outdoor flat road surfaces and outdoor bumpy road surfaces.
Background
Existing Wi-Fi positioning techniques typically use triangulation based on received signal strength indications, signal time of arrival and angle of arrival estimation, etc. to perform positioning. But almost all positioning methods are directed to the physical layer information of Wi-Fi signals, such as amplitude, frequency, time, angle, etc., and no relevant work is focused on the moving object itself, where: the positioning method adopting the inertial sensor cannot be used in an indoor environment with a poor network condition; the indoor positioning method based on the received signal strength indication is easily affected by path attenuation, shielding and multipath effects, and the positioning result is not accurate enough.
Disclosure of Invention
Aiming at the defects of the prior positioning technology, the invention provides a wheeled moving target high-precision positioning system and method based on wireless signals by fully utilizing the advantage of wheel rotation according to the observation of using wheels to move most of moving targets.
The invention is realized by the following technical scheme:
the invention relates to a high-precision wheel type mobile target positioning system based on wireless signals, which comprises: the Wi-Fi positioning system comprises a signal state information acquisition module for receiving Wi-Fi signals, a sensing calculation module for inertial sensing and executing a positioning algorithm, and power modules respectively connected with the sensing calculation module and the power modules, wherein: the signal state information acquisition module receives wireless channel state information and transmits the information to the sensing calculation module, and the sensing calculation module takes the received wireless channel information as the input of a positioning algorithm and obtains the current position of the target through calculation.
The signal state information acquisition module comprises: constitute the antenna array of regular triangle structure and be used for connecting the slewing mechanism of antenna array and wheel by three antennas and antenna pedestal, wherein: the antenna array and the wheel rotate synchronously through the rotating mechanism and extract channel state information from the received Wi-Fi signals.
The antenna pedestal is a regular triangle assembly and is designed and manufactured by adopting a 3D printing technology, an antenna mounting hole is reserved on each corner of the antenna pedestal, the distance between every two adjacent antenna mounting holes is 6cm, namely, the distance is less than the half wavelength of 2.4GHz Wi-Fi signals, the three antennas are tightly fixed in the holes through the antenna pedestal, and the interval of the three antennas is ensured to be unchanged when the wheel rotates at a high speed; when installed, it is first ensured that one antenna is aligned with the center of the wheel and the direction of the antenna is perpendicular to the plane of the wheel, and when the wheel starts to rotate, the antenna array rotates accordingly.
The sensing calculation module comprises: the device comprises an inertial sensor used for collecting motion information as input of wheel type moving target positioning to construct a space-time antenna array and a control unit used for carrying out wheel type moving target positioning in real time.
The power module includes: the sensor comprises a main power supply unit, a secondary power supply unit connected with the main power supply unit, and a tertiary power supply unit respectively connected with the main power supply unit and a sensing calculation module, wherein: the main power supply unit directly provides energy for the sensing and calculating module; the secondary power supply unit is a solar battery wound on the antenna pedestal; the three-level power supply unit is a generator charger and is used for converting kinetic energy generated by wheel rotation into electric energy of the system and providing correction information for the positioning system.
The power module utilizes solar energy and kinetic energy generated by wheel rotation to realize self-power supply of the system, so that the system can be used for non-electric wheel-type moving objects such as bicycles and wheelchairs.
The invention relates to a positioning method of the system, which utilizes an antenna array and signal arrival angle estimation to carry out static positioning when a wheel is in a static state, respectively adopts translational positioning or differential positioning when an object moves, namely the wheel is in a rotating state, and finally uses inertial correction as compensation to further improve the local precision of the translational positioning and the differential positioning.
The static positioning specifically includes: by calculating azimuth angles given that the three antennas of the antenna array are not collinear
And a polar angle theta, the positioning being achieved by a single wireless router according to the radius R of the wheel and the center of the wheel being located on a ray of a wireless signal emitted by the wireless router in the direction of arrival of the signal.
The translational positioning specifically refers to: when the terrain is flat, the characteristics of the antenna array moving along with the wheels are utilized, a plurality of virtual antennas are obtained through sampling, the distribution of multipath including the number of signals from a plurality of paths, the arrival angles of the signals and the relative power is obtained through positioning calculation of the track-based synthetic aperture radar, and then the shortest path is selected based on the arrival time of the signals.
The virtual antenna is as follows: the spatial position of the antenna array at each sampling time is specifically as follows: based on the motion of the wheel, the track of the first antenna in the antenna array is a straight line, and the track of the second antenna and the track of the third antenna are cycloids with the height of 2R and the width of 2 pi R respectively, wherein: r is the distance between the antennas and R is the radius of the wheel.
The track-based positioning calculation of the synthetic aperture radar refers to: for the first in the antenna arrayAn antenna, which is constructed by a linear synthetic aperture radar to establish a virtual antenna array when going from a wireless router to A 1 (t 1 ) Is d, t i Is the time for collecting the ith sample, and n is the number of virtual antennas (i is more than or equal to 1 and less than or equal to n); according to the basic channel model will be transmitted by antenna A 1 At t i Time-measured radio channel h 1i Is a plurality of
Wherein: omega is the angular velocity of the wheel, t is the time, h 1i Containing multipath combining information, but only one h i It is not sufficient to deduce all paths. As long as the number n of virtual antennas is greater than the number of multipaths, the linear synthetic aperture radar can calculate the relative power of the signal (e.g., θ from 0 to 2 π) along all angles to produce a differentiable multipath profile. Since there is no a priori knowledge of the number of multipaths, a relatively large n is employed to ensure that the equation is solvable. A. The 1 Relative power P along angle theta 1 (theta) may be
For the second and third antennas of the antenna array, rotation of the wheel is achieved by a cycloidal synthetic aperture radar: antenna A 2 At t i Time-measured radio channel h 2i Is composed of
Wherein: f. of l (t i )＝Rω(t i -t 1 ) sin theta is linear motion antenna A 2 The resulting influence f r (t i )＝rcos(θ+ω(t i -t 1 ) Is a circular motion to the antenna A 2 The resulting effect. Thus, the antenna A 2 Relative power P along angle theta 2 (θ) can be { [ MEANS ]>
In the same way, will h 2i And A 2 Is replaced by h 3i And A 3 Then P is obtained 3 (θ)。
The differential positioning means that: when the terrain is complex and the translational positioning cannot work, the antenna array follows the straight line from L α Move to L β To L γ ；L α And L β A distance of l therebetween αβ ，L β And L γ Is a distance of l βγ Remember of αβ /l βγ = k; when alpha, beta and gamma are L respectively α 、L β And L γ Angle of incidence of; deriving relationships from geometric knowledge
Further obtain (1+k) tan beta-tan (2- αβ -β)-ktan(2∠ βγ - β) =0; due to the fact that αβ 、∠ βγ And k are known, so that beta can be calculated by the above formula, and then alpha and gamma can be calculated; and after the incident angle and the position are in one-to-one correspondence, the shortest path is selected based on the signal arrival time. />
The selection of the shortest path based on the signal arrival time includes: when no barrier exists between the wireless router and the antenna array, only the angle with the highest relative power needs to be selected as a direct path; however, in practical situations, the power of the direct path may be attenuated, even if only the indirect path is available; in this case, the number of paths and their incident angles are determined according to the multi-path distribution, but it is impossible to determine which is a direct path; the shortest time is used from the wireless router to the antenna array through the direct path among all paths; according to this feature, an attempt is made to find the path with the smallest signal arrival time, which is either the direct path or the indirect path closest to the direct path; the basic idea is to use two positions to calculate the signal arrival times of all possible paths; when the antenna array is moved from position 1 to position 2, wherein: the distance between the two positions is l; after the incidence angle is obtained through the synthetic aperture radar technology, the possible position of the wireless router is found through reversely extending rays; two paths at position 1 are then calculated using the following equationτ 1 And τ 2 Signal arrival time of (a):
wherein: c is the velocity of the electromagnetic wave, θ 11 、θ 12 The included angle theta between the wireless signal sent by the wireless router and the wireless signal sent by the virtual wireless router at the position 1 and the vertical direction 21 、θ 22 Included angles between wireless signals sent by the wireless router and the virtual wireless router at the position 2 and the vertical direction are respectively included; when T is 1 <T 2 Then, consider θ 11 Is the correct angle of incidence and T 1 Is the signal arrival time.
In an actual mobile scene, a direct path between the wireless router and the wheel cannot be guaranteed to exist all the time. When an indirect path occurs, even if the shortest path is found using the method proposed above, this is only the reflected path closest to the direct path. The use of an indirect path for positioning may result in large errors, and therefore the present invention designs inertial correction to compensate for the errors introduced by the indirect path.
The inertial correction is as follows: detection of an indirect path by comparing the similarity of two trajectories, one being trajectory T generated using Wi-Fi signals by translational positioning or differential positioning W The other is a track T generated by an inertial sensor using dead reckoning S . The invention leads the track T W And T S The segments are divided according to the time stamp, and then the slope change of the trace within each segment is calculated. When T is W Slope change and T in S If the slope change in (b) is relatively large, an indirect path is considered to have occurred in that time period.
To correct for errors resulting from indirect paths, further use is made of T S To T W And (6) compensating. Firstly, let T W Wherein a segment deletion of the indirect path is detected. Then from T S The segment corresponding to the deleted segment is taken out and adjustedIts angle and appropriate scaling. Finally filling the adjusted segment into T W So that the trajectory is continuous and free of abrupt changes. Through the above steps, T S For T W Is compensated so that T W The method is closer to the actual running track, and reduces the error generated by the indirect path.
Technical effects
Compared with the prior art, the invention fully utilizes the characteristic of wheel rotation, provides the WiFi-based high-precision positioning system for the wheel type moving target, and the positioning precision can reach within 1 meter under three environments of indoor, outdoor flat road surfaces and outdoor bumpy road surfaces.
The invention realizes the self-power supply of the system by utilizing the solar energy and the kinetic energy generated by the rotation of the wheels, when the target is in an indoor environment, the kinetic energy generated by the rotation of the wheels is mainly utilized to supply power for the system, and when the target is in an outdoor environment, the kinetic energy generated by the rotation of the wheels and the solar energy are utilized to supply power for the system together.
Drawings
FIG. 1 is a schematic diagram of the system of the present invention;
FIG. 2 is a flow chart of a positioning algorithm;
FIG. 3 is a schematic view of an incident angle in 3D coordinates;
FIG. 4 is a comparison of a wheeled mobile object positioning system with other positioning systems;
Detailed Description
The invention relates to a control method of the system, which comprises the following steps: static positioning, translational positioning, differential positioning and inertial correction, specifically:
1) When the wheel is in a static state, static positioning is adopted, an antenna array and signal arrival angle estimation are fully utilized, otherwise:
2) When the object moves, namely the wheel is in a rotating state, further judging that:
2.1 The terrain is flat, if flat, translational positioning is adopted to obtain higher precision;
2.2 When the terrain is complex and the translational positioning cannot work, the differential positioning is adopted to ensure the positioning accuracy.
After positioning using translational positioning or differential positioning, inertial correction is employed as compensation to further improve the local accuracy of the translational positioning and the differential positioning.
As shown in FIG. 3, the initial state of the antenna array of the wheeled mobile object positioning system is A 1 At the upper right, A 2 At the lower left, A 3 Is located below. Because of the antenna A 1 ，A 2 And A 3 Not collinear, so azimuth can be calculated
And a polar angle theta. Since the radius R of the wheel is known and the center of the wheel is located on the line of sight of the wireless signal emitted by the wireless router in the direction of arrival of the signal, static positioning can be achieved using a single wireless router.
When the object is moving, i.e. the wheels are in rotation, and the terrain is flat, translational positioning is chosen for higher accuracy. A large number of virtual antennas are obtained by utilizing the motion of the antennas, and then a positioning method of the synthetic aperture radar based on the track is designed. The distribution of the multipaths, including the number of signals from the multiple paths, the angle of arrival of the signals, and the relative power, is then calculated. And finally, selecting the shortest path as a direct path through signal arrival time estimation.
Antenna A 1 Is a straight line, and the antenna A 2 And A 3 Are cycloids with a height of 2R and a width of 2 pi R, wherein: r is the distance between the antennas and R is the radius of the wheel. For antenna A 1 The system uses linear synthetic aperture radar to establish a virtual antenna array. When going from the wireless router to A 1 (t 1 ) Is d, t i Is the time when the ith sample is acquired, and n is the number of virtual antennas (1 ≦ i ≦ n). According to the basic channel model will be transmitted by antenna A 1 At t i Time-measured radio channel h 1i Is a plurality of
Wherein: ω is the angular velocity of the wheel and t is time. H is 1i Containing multipath combining information, but only one h i It is not sufficient to deduce all paths. As long as the number n of virtual antennas is greater than the number of multipaths, the linear synthetic aperture radar can calculate the relative power of the signal (e.g., θ from 0 to 2 π) along all angles to produce a differentiable multipath profile. Since there is no a priori knowledge of the number of multipaths, a relatively large n is employed to ensure that the equation is solvable. A. The 1 Relative power P along angle theta 1 (θ) can be { (E) }>
For antenna A 2 And A 3 The system specially designs the cycloidal synthetic aperture radar for the rotation of the wheel. Antenna A 2 At t i Time-measured radio channel h 2i Is composed of
Wherein: f. of l (t i )＝Rω(t i -t 1 ) sin theta is linear motion antenna A 2 The resulting influence of f r (t i )＝rcos(θ+ω(t i -t 1 ) Is a circular motion to the antenna A 2 The resulting effect. Thus, the antenna A 2 Relative power P along angle theta 2 (θ) can be { (E) }>
In the same way, will h 2i And A 2 Is replaced by h 3i And A 3 Then P is obtained 3 (θ)。
There have been many studies focusing on shortest path selection for the multipath problem. Aiming at a wheel type mobile target positioning system, the invention designs shortest path selection based on signal arrival time, which is an enhanced method of direct path separation. When there is no obstacle between the wireless router and the antenna array, only the angle with the highest relative power needs to be selected as the direct path. However, in practical situations, the power of the direct path may beMay be attenuated or even have an indirect path. In this case, the number of paths and their incident angles are determined according to the multi-path distribution, but it is impossible to determine which is a direct path. Of all paths, the time used from the wireless router to the antenna array via the direct path is the shortest. According to this feature, an attempt is made to find the path with the smallest signal arrival time, which is either the direct path or the indirect path closest to the direct path. The basic idea is to use two positions to calculate the signal arrival times of all possible paths. When the antenna array is moved from position 1 to position 2, wherein: the distance between the two positions is l. After obtaining the angle of incidence by synthetic aperture radar technology, the possible locations of the wireless router are found by extending the rays backwards. The two paths τ at position 1 are then calculated using the following equation 1 And τ 2 Signal arrival time of (c):
wherein: c is the velocity of the electromagnetic wave, θ 11 、θ 12 The included angle theta between the wireless signal sent by the wireless router and the wireless signal sent by the virtual wireless router at the position 1 and the vertical direction 21 、θ 22 The included angles between the wireless signals sent by the wireless router and the virtual wireless router at the position 2 and the vertical direction are respectively. When T is 1 <T 2 Then, consider θ 11 Is the correct angle of incidence and T 1 Is the signal arrival time.
A wrong wireless router may be encountered during actual use. To address this problem, the present invention adds more multipath profiles at different locations to guess at the likely wireless router. Second, two adjacent locations may have different numbers of paths due to changes in the external environment. To avoid this, the present system divides the results of the measurements into a plurality of windows. The coarse-grained window is divided according to the switching between wireless routers. When a handover occurs, the actual wireless router location changes even though the number of multipaths remains the same, and should be recalculated at this time. The fine-grained window is divided according to the change of the path. Consecutive measurements with the same number of paths are divided into one window. The combination of multiple measurements is limited to the same window. Third, in complex environments, especially in indoor scenarios, there are a large number of paths in the space, which can result in excessive computational overhead. Therefore, the invention directly abandons the calculation of two incidence angles with larger power difference, which effectively reduces a part of the overhead.
When the wheel is in rotation, the relative motion between any two antennas is circular, although the motion of a single antenna is linear or cycloidal. The track of each antenna calculated by the inertial sensor is not very accurate and is seriously influenced by the terrain. Unlike these trajectories, however, the trajectory of the relative motion between each two antennas is a circle of radius r, because the relative motion is subtracted from the two trajectories, thereby canceling out the effect of the terrain. In addition, the time per wheel revolution may be measured by an internal landmark. The only thing that needs to be known is the distribution of the virtual antennas on a circle. In an ideal case, when the wheel rotates at a constant angular velocity ω, the virtual antennas are evenly distributed on a circle. When the angular velocity is varied, the distribution of the antenna can be accurately recovered using the data collected by the gyroscope. For the above reasons, the present invention designs differential positioning.
The antenna array follows a straight line from L α Move to L β To L γ 。L α And L β Is a distance of l αβ ，L β And L γ Is a distance of l βγ Remember l αβ /l βγ K (= k). When alpha, beta and gamma are L respectively α 、L β And L γ Angle of incidence. Deriving relationships from geometric knowledge
Further obtain (1+k) tan beta-tan (2 & lt) αβ -β)-ktan(2∠ βγ - β) =0. Due to the fact that αβ 、∠ βγ And k are known, so using the above formula, β can be calculated, and further α and γ can be calculated. After the incident angle is in one-to-one correspondence with the position, a path is selected from a plurality of pathsThe shortest path method is the same as differential positioning.
In an actual mobile scene, a direct path between the wireless router and the wheel cannot be guaranteed to exist all the time. When an indirect path occurs, even if the shortest path is found using the method proposed above, this is only the reflected path closest to the direct path. The positioning using the indirect path may cause a large error, so the present invention designs an inertial correction to compensate the error caused by the indirect path.
The invention detects the indirect path by comparing the similarity of the two tracks. When T is W Is a track, T, generated using Wi-Fi signals by translational positioning or differential positioning S Is a track generated by inertial sensors using dead reckoning. The invention leads the track T W And T S The segments are divided according to the time stamp, and then the slope change of the trace within each segment is calculated. When T is W Slope change and T in S If the slope change in (b) is relatively large, an indirect path is considered to have occurred in that time period.
To correct for errors resulting from indirect paths, the present invention uses T S To T W Compensation is performed. Firstly, let T W Wherein a segment deletion of the indirect path is detected. Then from T S The segment corresponding to the deleted segment is fetched, its angle is adjusted and appropriate scaling is performed. Finally filling the adjusted segment into T W So that the trajectory is continuous and free of abrupt changes. Through the above steps, T S For T W Is compensated for so that T W The method is closer to the actual running track, and reduces the error generated by the indirect path.
The present embodiment is based on a test platform consisting of a bicycle and system hardware, and numerous experiments were performed both indoors and outdoors to evaluate the performance of a wheeled mobile target positioning system. This example was carried out in three main scenarios, indoor, outdoor flat and outdoor bumpy road. For an indoor environment, 8 wireless routers were installed on the ceiling. It should be noted that there are many walls in this environment, so there are many paths that are not negligible. For an outdoor flat road surface, a flat rectangular area 34.5m × 7.5m is selected in the present embodiment. Red markers are used to define the experimental area while facilitating the measurement. In addition, four wireless routers are deployed at equal intervals near the window of the second floor, and the wheeled mobile object positioning system can freely switch among the wireless routers. For outdoor bumpy roads, the present embodiment uses irregular areas to test the performance of a wheeled moving-object locating system on outdoor bumpy roads. The present embodiment obtains the parameters of complex terrain by accurately measuring the length, width, and height of the stairs and slopes, and simulates bumpy terrain using a bicycle to walk up and down the stairs.
This embodiment sets three speeds for the bicycle:
1) And (3) standing: the speed of the bicycle is 0km/h.
2) The walking speed is as follows: the user pushes the bicycle to walk forward, and the speed is varied within the range of 0 to 5km/h.
3) The running speed is as follows: the user rides the bicycle forward with a speed varying in the range of 5 to 15km/h.
When the wheel is at rest, static positioning is used. When the object is moving, i.e. the wheels are in rotation, on outdoor flat road surfaces, translational positioning is used for obtaining higher precision; when the device is arranged on an outdoor bumpy road surface, the positioning accuracy is ensured by adopting differential positioning. Finally, the inertia correction is used as a compensation for further improving the local precision of the translational positioning and the differential positioning.
On indoor and outdoor flat roads, three speeds occur and their time ratios are 1. But when tested on outdoor bumpy roads, only static and walking speeds occurred, and their time ratio was 1:9.
In addition, in this embodiment, the transmission power of the wireless router is 20dBm (100 mW), and each wireless router broadcasts 200 packets per second. The sampling rate of the inertial sensor is 200Hz. During the course of the experiment in this example over 100 hours, there were occasional instances where there was only an indirect path due to interference caused by obstacles and pedestrians.
The wheel type moving target positioning system has good performance in all experimental scenes, and the average positioning precision reaches 88cm. As shown in fig. 4, by combining various positioning technologies, such as static positioning, translational positioning, differential positioning and inertial correction, the wheeled mobile target positioning system is superior to the existing positioning systems in terms of accuracy and stability, such as global positioning system, arraytack (paper entitled "arraytack: a fine-oriented positioning system", author Jie Xiong, etc., published in international conference useneix NSDI in 2013) and unicase (paper entitled "accu index localization with zero start-up cost", author swarn Kumar, etc., published in international conference ACM MOBICOM in 2014).
The correct judgment of the environment and the selection of a proper positioning technology are also the key for realizing the positioning of the wheeled moving target. When the target is in a static state, the wheel type moving target positioning system can always judge correctly. However, there is some confusion regarding the resolution of outdoor flat and rough road surfaces, which may result in the selection of a location technique that is not optimal. When only an indirect path exists, the detection is carried out by comparing the tracks of the translational positioning or differential positioning and dead reckoning positioning method, and the accuracy can reach 97%. In summary, the wheeled mobile target positioning system can accurately determine most scenes and select the most suitable positioning technology.
The power supply design is also one of the key points of the wheel type moving target positioning system. When the target is in an indoor environment, the generator is influenced by the speed of the vehicle and has low efficiency, and the solar cell has low effect due to no strong light, so the solar cell is mainly powered by a mobile power supply. The power module of this embodiment can support about 6 hours of laboratory experiments. In contrast, in an outdoor environment, the contribution of the generator is slightly increased due to the faster outdoor operating speed, the main power supply comes from the solar cell, and the mobile power supply supplies power only when needed. With sufficient sunlight, wheeled mobile object positioning systems may continue to operate for days.
The foregoing embodiments may be modified in many different ways by one skilled in the art without departing from the spirit and scope of the invention, which is defined by the appended claims and not by the preceding embodiments, and all embodiments within their scope are intended to be limited by the scope of the invention.
Claims (10)
1. A wheeled moving target high-precision positioning system based on wireless signals is characterized by comprising: the Wi-Fi positioning system comprises a signal state information acquisition module for receiving Wi-Fi signals, a sensing calculation module for inertial sensing and executing a positioning algorithm, and power modules respectively connected with the sensing calculation module and the power modules, wherein: the signal state information acquisition module receives wireless channel state information and transmits the information to the sensing calculation module, and the sensing calculation module takes the received wireless channel information as the input of a positioning algorithm and obtains the current position of a target through calculation;
the signal state information acquisition module comprises: constitute the antenna array of regular triangle structure and be used for connecting the slewing mechanism of antenna array and wheel by three antennas and antenna pedestal, wherein: the antenna array and the wheels synchronously rotate through the rotating mechanism and extract channel state information from the received Wi-Fi signals;
the positioning algorithm comprises translational positioning or differential positioning based on positioning calculation of the track synthetic aperture radar;
the track-based positioning calculation of the synthetic aperture radar refers to: for the first antenna in the antenna array, a virtual antenna array is established by linear synthetic aperture radar when going from the wireless router to A 1 (t 1 ) Is d, t i Is the time for collecting the ith sample, n is the number of virtual antennas, i is more than or equal to 1 and less than or equal to n; according to the basic channel model will be transmitted by antenna A 1 At t i Time-measured radio channel h 1i Is a plurality of
Wherein: r is the wheel radius, omega is the angular velocity of the wheel, t is the time, h 1i Combined information including multiple paths, A 1 Along the cornerRelative power P of degree theta 1 (θ) can be P 1 θ＝/>
Theta is a polar angle;
for the second and third antennas of the antenna array, rotation of the wheel is achieved by a cycloidal synthetic aperture radar: antenna A 2 At t i Time-measured radio channel h 2i Is composed of
Wherein: f. of l (t i ) = Rω(t i -t 1 ) sin theta is linear motion antenna A 2 The resulting influence f r (t i ) = rcos(θ+ω(t i -t 1 ) For circular motion to the antenna A 2 The resulting effect is that the antenna A 2 Relative power P along angle theta 2 (θ) can be { [ MEANS ]>
In the same way, will h 2i And A 2 Is replaced by h 3i And A 3 Then P is obtained 3 (θ), r is the distance between the antennas.
2. The high-precision wheel-type moving target positioning system of claim 1, wherein the antenna base is a regular triangle assembly, is designed and manufactured by using 3D printing technology, and is provided with an antenna mounting hole at each corner, the distance between two adjacent antenna mounting holes is 6cm, namely less than half wavelength of 2.4ghz wi-Fi signal, and the three antennas are tightly fixed in the holes through the antenna base, so that the spacing of the wheels is kept constant during high-speed rotation.
3. The system for high-precision positioning of wheeled mobile objects as claimed in claim 1, wherein said sensing and calculating module comprises: the system comprises an inertial sensor used for collecting motion information as input of wheel type moving target positioning to construct a space-time antenna array and a control unit used for real-time wheel type moving target positioning.
4. The system for high-precision positioning of wheeled moving objects as claimed in claim 1, wherein said power module comprises: main power supply unit, the second grade power supply unit who links to each other with main power supply unit and the tertiary power supply unit who links to each other with main power supply unit and sensing calculation module respectively, wherein: the main power supply unit directly provides energy for the sensing calculation module; the secondary power supply unit is a solar battery wound on the antenna pedestal; the three-level power supply unit is a generator charger and is used for converting kinetic energy generated by wheel rotation into electric energy of the system and providing correction information for the positioning system.
5. A positioning method based on the system of any one of the preceding claims, characterized in that the antenna array and the signal arrival angle estimation are used for static positioning when the wheel is in a static state, and for translational positioning or differential positioning when the object is moving, i.e. the wheel is in a rotating state, respectively, and finally the local accuracy of the translational positioning and the differential positioning is further improved by using inertial correction as compensation.
6. The method according to claim 5, wherein said static positioning is specifically: by calculating azimuth angles given that the three antennas of the antenna array are not collinear
And a polar angle theta, according to the radius R of the wheel and the center of the wheel is positioned on the ray of the wireless signal emitted by the wireless router along the signal arrival direction, and the positioning is realized by a single wireless router.
7. The method according to claim 5, wherein said translational positioning is in particular: when the terrain is flat, the characteristics of the antenna array moving along with the wheel are utilized, a plurality of virtual antennas are obtained through sampling, the distribution of multipath including the number of signals from a plurality of paths, the arrival angles of the signals and the relative power is obtained through the positioning calculation of the synthetic aperture radar based on the track, and then the shortest path is selected based on the arrival time of the signals.
8. The method of claim 5, wherein said differentially positioning is by: when the terrain is complex and the translational positioning cannot work, the antenna array follows the straight line from L α Move to L β To L γ ；L α And L β Is a distance of l αβ ，L β And L γ Is a distance of l βγ Remember l αβ /l βγ K (= k); when alpha, beta and gamma are L respectively α 、L β And L γ Angle of incidence of; deriving relationships from geometric knowledge
Further obtain (1+k) tan beta-tan (2 & lt) αβ -β)-ktan(2∠ βγ - β) =0; calculating beta to further calculate alpha and gamma; and after the incident angle and the position are in one-to-one correspondence, the shortest path is selected based on the signal arrival time.
9. The method according to claim 7 or 8, wherein said selecting the shortest path based on signal arrival time is: when the antenna array is moved from position 1 to position 2, wherein: the distance between the two positions is l; after the incidence angle is obtained through the synthetic aperture radar technology, the possible position of the wireless router is found through reversely extending rays; then using two paths τ at computed position 1 1 And τ 2 Signal arrival time of (a):
wherein: c is the velocity of the electromagnetic wave, θ 11 、θ 12 The included angle theta between the wireless signal sent by the wireless router and the wireless signal sent by the virtual wireless router at the position 1 and the vertical direction 21 、θ 22 Respectively wireless router and virtual noneThe included angle between the wireless signal sent by the router and the vertical direction at the position 2; when T is 1 <T 2 Then, consider θ 11 Is the correct angle of incidence and T 1 Is the signal arrival time.
10. The method according to any one of claims 5 to 8, wherein said inertial correction is: detection of an indirect path by comparing the similarity of two trajectories, one being trajectory T generated using Wi-Fi signals by translational positioning or differential positioning W The other is a track T generated by an inertial sensor using dead reckoning S (ii) a Will track T W And T S Dividing the time stamp into a plurality of segments, and calculating the slope change of the trace in each segment when T is W Slope change and T in S If the slope change in the segment is large, the indirect path is considered to appear in the segment;
to correct for errors resulting from indirect paths, further use is made of T S To T W And (3) compensation is carried out: will T W Detecting segment deletion of the indirect path; then from T S Taking out the segment corresponding to the deleted segment, adjusting the angle of the segment and carrying out proper scaling; finally filling the adjusted segment into T W So that the trajectory is continuous and free of abrupt changes; t is a unit of S For T W Is compensated so that T W The method is closer to the actual running track, and reduces the error generated by the indirect path.
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