Patent Application
20140375495
This invention relates to a positioning system, and in particular to a positioning system for vehicles.
Navigation and positioning systems are in common use, for example using one of the available Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS). In such systems, a user device receives signals from multiple satellite vehicles, each of which has a predetermined trajectory. As a result, the user device is able to make measurements on the received signals, and is able to use these to provide estimates of the user's position and velocity.
One well-known problem with such systems is that signals from the satellite vehicles can arrive at the user device after being reflected off, or refracted by, obstacles that are in the line-of-sight path between the satellite vehicle and the user device or are close to the line-of-sight path. These obstacles can also have the effect that the direct line-of-sight signal is attenuated significantly, possibly to the extent that the user device is practically unable to receive it.
The effect of this problem can be that the user device is unable to make good estimates of the user's position and velocity.
U.S. Pat. No. 7,702,459 describes a positioning system, for use in an environment in which the system may receive multipath signals as a result of reflections. In the described system, GPS measurements are compared with the position and velocity of the device as currently estimated based on earlier GPS measurements. Measurements that are inconsistent with the current estimate (for example because they are based on reflected signals) can be regarded as outliers, and disregarded when generating the next estimate of the position and velocity of the device. This assumes that the system can have no knowledge of the potential obstacles, and hence of the effects of reflection on the received signals.
According to one aspect of the present invention, there is provided a method of operation of a positioning system. An estimate is obtained of the heading of a body whose position or velocity is to be estimated. Respective signals from a plurality of transmitters are tracked, and a respective Doppler measurement is obtained from each of said tracked signals. For each of the tracked signals, a speed of the body is estimated using the estimate of the heading of the body and the respective Doppler measurement, and it is determined whether the estimated speed of the body is consistent with the signal having been received along a direct path from the transmitter. Signals that provide information about the speed of the body that is inconsistent with the signal having been received along a direct path from the transmitter, are then disregarded when estimating the position or velocity of the body.
The method may include determining whether the estimated speed of the body is consistent with the signal having been received along a direct path from the transmitter by determining whether the estimated speed of the body suggests that the respective signal was obtained from the transmitter via a reflection.
The method may include determining whether the estimated speed of the body is consistent with the signal having been received along a direct path from the transmitter by comparing the estimated speed of the body in the direction of said estimated heading with a threshold speed.
The threshold speed may be zero, such that it is determined that the estimated speed of the body is not consistent with the signal having been received along a direct path from the transmitter if the estimated speed of the body in the direction of said estimated heading is negative.
The threshold speed may be adaptable, based on an angle between the estimated heading of the body whose position or velocity is to be estimated and the direct path from the transmitter.
The estimate of the heading of the body may be based on a signal received from a heading sensor provided on the body.
The signal from the heading sensor may further comprise information about the speed of the body, and wherein the method comprises determining whether the estimated speed of the body obtained using the estimate of the heading of the body and the respective Doppler measurement is consistent with the signal having been received along a direct path from the transmitter by comparing said estimated speed of said body obtained using the estimate of the heading of the body and the respective Doppler measurement with the information about the speed of the body obtained from the heading sensor.
The estimate of the heading of the body may be obtained immediately after determining that the body has started moving after being determined to be stationary.
The method may further comprise preventing future tracking of disregarded signals.
Measurements from the signals that are not disregarded may be used to update a position/velocity/time solution for the body.
The heading sensor may comprise a gyroscope, having a known positional relationship to the body, for indicating an orientation of the body, and may then further comprise a temperature sensor, for calibrating an output of the gyroscope.
The heading sensor may comprise an accelerometer or a magnetometer, for indicating a direction of motion of the body.
According to a second aspect of the invention, there is provided a positioning system, having a heading sensor, for generating an estimate of the heading of a body whose position or velocity is to be estimated, and a receiver, for detecting signals from a plurality of transmitters. The system also includes a processor, for performing a method according to the first aspect of the invention.
Preferred embodiments will now be described, by way of example only, with reference to the accompanying drawings, in which:—
The navigation and positioning system is shown in
The electronic device 10 also includes at least one additional sensor 16, as described in more detail below.
The GNSS chipset 12 includes a radio frequency (RF) front end circuit 22, for receiving signals transmitted by satellite vehicles. Received signals are passed to software in the form of a measurement engine 24, which can be thought of as comprising a tracking controller 26 and a measurement processor 28. The tracking controller 26 controls the operation of the RF front end circuit so that it receives the intended signals from the satellite vehicles, and the measurements required for determining the position and velocity of the device are extracted by the measurement processor 28.
The host processor 14 runs software in the form of a positioning engine 32, which includes a controller 34 and a position-velocity-time (PVT) processor 36. The controller 34 coordinates the positioning engine 32 and the measurement engine 24, while the PVT processor 36 calculates an estimate of the position and velocity of the device, and the time, using the measurements received from the GNSS chipset 12 and from the additional sensor 16. While the invention is described herein with reference to its use in a GNSS satellite navigation and positioning system, it can equally be used in other systems in which a device receives signals from transmitters whose position (and velocity, if appropriate) is known. For example, such transmitters might take the form of GNSS pseudolites, Indoor Messaging System (IMES) transmitters, Bluetooth transmitters, WiFi transmitters, cellular wireless transmitters, or near field communication (NFC) transmitters.
As is generally understood, the RF front end circuit 22 is controlled so that it receives signals from multiple transmitters, such as satellite vehicles in the illustrated example. Measurements are extracted from these signals by the measurement engine 24, and supplied to the positioning engine 32, which then calculates an estimate of the position and velocity of the device, and the time.
Typically, the measurements relate to the times at which signals are received by the receiver. If the receiver has a clock that is known to be completely synchronised to the satellites' time, the time at which a signal is received will indicate the distance of the receiver from the satellite vehicle, i.e. the range. By obtaining range measurements from three or more satellite vehicles, the position of the receiver can be calculated. In practice, most navigation devices do not have such a clock, and so the time offset is one of the parameters that is sought to be calculated, by using additional measurements relating to the times at which signals are received. Range measurements computed using an un-synchronised receiver clock are referred to as pseudoranges. Typically, pseudorange measurements from four or more satellite vehicles are used to calculate the three-dimensional position of the receiver together with the receiver clock time offset.
The measurements may also relate to the phase of the carrier wave of each signal received from a satellite. This provides additional information that can be used when calculating the position and velocity of the device, and the time.
The movement of the device 10 causes Doppler effects in the signals received by the receiver. That is, the frequency of received signals can be compared with the frequency of a local oscillator in the RF front end circuit 22. The apparent frequency of the received signals is shifted by an amount that depends on the component of the speed of movement of the device towards or away from the satellite. It also depends on the error of the frequency of the local oscillator relative to the satellites' time-frame. The effect of the local oscillator's frequency error on the Doppler measurements is analogous to the effect of the receiver's time offset on the range measurements. However, the Doppler measurements are usually still referred to as ‘Doppler’ rather than ‘pseudo-Doppler’. The Doppler measurements can be used to calculate the velocity of the movement of the device 10. Typically, Doppler measurements from four or more satellite vehicles are used to calculate the three-dimensional velocity of the receiver together with the receiver clock frequency offset. It is also possible to use repeated Doppler measurements to determine the position of the device 10. For example, if the Doppler measurements at one time are used to calculate the velocity of the device 10, this can be used to estimate the movement of the device in the period until the next Doppler measurements are taken, and successive repetitions of this process can be used to obtain an estimate of the path followed by the device.
Specifically,
As mentioned above, the vehicle 50 is moving at a speed S, in a direction that is on the straight line between the building 52 and the first satellite vehicle 62, towards the first satellite vehicle 62.
The movement of the vehicle 50 causes Doppler effects on the signals received by the GNSS chipset 12, and these effects can be used to generate Doppler measurements. A Doppler measurement is taken in general terms to mean a rate of change of the pseudorange of the user from the satellite vehicle. This discussion assumes that the Doppler effects caused by movement of the satellite vehicle have been removed. However, it is assumed that each Doppler measurement will still be subject to error caused by an offset in the frequency of the signals generated by the oscillator in the RF front end circuit of the GNSS chipset.
As described above,
Therefore, when the vehicle 50 is moving towards the satellite vehicle 60, that is, to the right in
Thus
In
In
As another example, the line 82 corresponds to the range of cases in which the vehicle is moving directly towards the reflector, and thus the vehicle's speed has a component (in the range from 0 to S) in the direction towards the satellite vehicle, but has a speed of S in the direction towards the reflector, and so the Doppler measurement overestimates the vehicle's velocity.
As a further example, the line 84 corresponds to the cases in which the vehicle is moving directly towards the satellite vehicle (and therefore has a speed S in that direction), for different positions of the reflector. Thus, a reflector directly “behind” the vehicle (as seen from the satellite vehicle) causes an error of −2S in the Doppler measurement, while a reflector that is directly adjacent to the line-of-sight path between the satellite vehicle and the vehicle causes a very small error in the Doppler measurement.
It is important for the purposes of the method described herein to recognise that, when the vehicle's speed is zero, the presence of a reflector causes no error in the Doppler measurement. (This is ignoring the small effects due to the change in geometry of the satellite-reflector-receiver resulting from the motion of the satellite.) It is also important to recognise that, regardless of the vehicle's direction of movement, and regardless of the shape and position of the reflector, the error in the Doppler measurement lies within the shaded parallelogram in
In one embodiment of the present invention, it is assumed that the electronic device 10 is mounted to the vehicle 50 in a generally fixed orientation. It may also be assumed that the direction of motion of the vehicle will generally be either substantially forwards or substantially backwards, with sideways movement being impossible.
Thus, the at least one additional sensor 16 can be used to estimate the direction of motion of the vehicle 50, and thus acts as a heading sensor. The additional sensor may include an accelerometer, and may additionally include a gyroscope and/or a magnetometer. The additional sensor may therefore be used to provide an estimate of the speed of the vehicle 50.
In
Thus, as described previously, if the vehicle is moving directly towards the satellite vehicle (that is, at a position of 0° on the horizontal axis), and there is a reflector directly “behind” the vehicle (as seen from the satellite vehicle) the Doppler measurement will result in an estimated speed of −1 unit, while a reflector that is directly adjacent to the line-of-sight path between the satellite vehicle and the vehicle will result in only a very small error in the Doppler measurement. Reflectors in other positions will result in estimated speeds in the range from −1 to +1 unit.
For other directions of movement of the vehicle (that is, at other positions on the horizontal axis), the use of a reflected signal can cause an even larger error in the estimated speed. In particular, when the vehicle is travelling in a direction that is at 90° to its line-of-sight path to the satellite vehicle, the use of a single Doppler measurement obtained from a reflected signal can produce an estimated speed that tends towards infinity, for certain reflector positions.
However, it will be noted that, in most cases, the speed estimate will be negative, or its magnitude will be under-estimated. Thus, if a reflected signal is used to estimate the speed of the user, and this estimate is used in turn to estimate the position of the moving user, this has the effect that the user appears to be “pushed back”, i.e. appears to have travelled a shorter distance than is really the case, either because the estimated magnitude of the speed is lower than the true value or because the direction of motion is reversed.
It will be noted in particular that, for many reflector positions, the speed that is estimated using a Doppler measurement obtained from a reflected signal is negative (i.e. it is in the opposite direction to the actual direction of movement of the vehicle). Thus, if the actual direction of movement of the vehicle is known, for example from a separate heading sensor provided on the vehicle, then it is easily recognised that the speed that is estimated using such a Doppler measurement is inconsistent with the known direction of movement. Thus, it can be determined from
If a separate speed sensor is also provided on the vehicle, then it is possible to identify other situations (corresponding to a wider range of reflector positions) in which it can be recognised that the speed that is estimated using a single Doppler measurement is inconsistent with the speed estimated from the additional sensor. In such situations, it can be determined from
The process starts in step 140 in which it is determined whether the vehicle is moving or stationary. This determination can be based on GNSS measurements and/or signals received from additional sensors such as a gyroscope, an accelerometer, or a magnetometer.
If it is determined that the vehicle is moving, the GNSS measurements and the gyroscope signals are combined in a sequential estimation process to provide estimates of the vehicle heading. If the sensors include an accelerometer, then the signals received therefrom can also be used in that estimation process. The measurements are also used in step 142 to update various functional or calibration parameters. For example, the sensors may also include a temperature sensor, in which case temperature measurements can be used in order to improve estimates of the coefficients of a temperature-dependent model of the gyroscope ‘zero-level’ offset, and the coefficients of a temperature-dependent model of the GNSS oscillator frequency offset.
More specifically, a gyroscope might produce an output signal that varies with temperature, and one way (out of many) in which this can be modelled is:
Rt=(G−A0−A1*T)*S+e
Rt is the true rotation rate,
G is the gyroscope output,
T is the temperature,
S is a scale factor,
e is the residual error, and
A0 and A1 are calibration coefficients.
By measuring the gyroscope output value at different temperatures, it is possible to obtain values for the coefficients A0 and A1, so that more accurate values can be obtained for the true rotation rate on subsequent measurement occasions.
Similarly, an oscillator in the RF front end circuit might produce an output signal at a frequency that varies with temperature, and one way (out of many) in which this can be modelled is:
Ft=Fa+B0+B1*T+e
Ft is the true frequency,
Fa is the nominal frequency,
T is the temperature,
e is the residual error, and
B0 and B1 are calibration coefficients.
By comparing the output frequency value with the frequency of received signals at different temperatures, it is possible to obtain values for the coefficients B0 and B1, so that more accurate values can be obtained for the true frequency on subsequent measurement occasions.
Thus, while the vehicle is moving, the GNSS and sensor measurements are combined in such a way as to calibrate the gyroscope relative to the vehicle. That is, parameters are estimated such that the data from the gyroscope alone can be used to estimate the heading of the vehicle. More specifically, the system learns which gyroscope signals are associated with movement of the vehicle. As discussed above, it will usually be the case that the vehicle will be travelling either forwards or backwards relative to its own axis, with a relatively small sideways component of movement. It will not necessarily be known initially how the device 10 is mounted in or on the vehicle, and so the output of the gyroscope will not initially be associated with movement in any particular direction of the vehicle, but this will become possible after such calibration.
If it is determined in step 140 that the vehicle is stationary, the process passes to step 144, in which ‘snapshot’ calibrations of the gyroscope zero-level offset and GNSS oscillator frequency offset are performed, making use of this ‘zero velocity’ knowledge.
Thus, by measuring the gyroscope output value at times when the true rotation rate is known to be zero, it is possible to obtain values for the coefficients A0 and A1 as defined above, so that more accurate values can be obtained for the true rotation rate on subsequent measurement occasions.
Similarly, by comparing the output frequency value with the known frequency of received signals at times when the vehicle is known to be stationary and so there is no Doppler error, it is possible to obtain values for the coefficients B0 and B1, so that more accurate values can be obtained for the true frequency on subsequent measurement occasions.
After this calibration, the process passes to step 146, in which it is determined whether the vehicle has started moving. If not, the process repeats step 144, until movement is detected, and the process passes to step 148.
In step 148, data from the gyroscope, or other heading sensor such as a magnetometer, together with estimates from a previous update of the vehicle heading and the various functional or calibration parameters, are used to predict the vehicle heading at the current time. The vehicle speed may also be estimated from the accelerometer data.
In addition, either at the same time or separately, the GNSS and (optionally) the temperature data, together with estimates from a previous update of the various functional or calibration parameters, are used to predict the GNSS oscillator frequency offset at the current time. The estimates from the previous update may be the estimates from the most recent stationary snapshot calibration performed in step 144, but other implementations are possible.
Thus, at the current update time, estimates of the user heading, clock drift and, optionally, speed are made, and these estimates are independent of, or only weakly-dependent on, the current GNSS measurements.
The process then passes to step 150, in which the latest GNSS measurements are considered. For example, these measurements might be sent from the measurement engine to the positioning engine in the case where the processing is split between these two modules.
As will be apparent, the RF front end will be receiving signals from multiple satellite vehicles. Where reflections are a factor, the RF front end will be receiving more than one signal from at least some satellite vehicles. Each signal can be used to generate a Doppler measurement.
As discussed previously, the Doppler measurements are affected by the error in the assumed frequency of the receiver's oscillator. By examining the frequencies of signals received when the receiver is known to be stationary, the frequency of the local oscillator signal can be calibrated. Then, any difference between the known frequency of the local oscillator and the frequency of a signal that is received when the receiver is known to be moving can be assumed to be due to that movement. Thus, the Doppler measurement can be used to estimate the component of the speed of the vehicle in the direction of the satellite vehicle in the horizontal plane, assuming any vertical velocity of the vehicle to be small. This can then be combined with knowledge of the direction of heading of the user relative to the direction of the satellite, in order to generate an estimate of the speed of the user in the direction of its heading. It will be recognised that such an estimate of the speed is unlikely to be particularly accurate, because of the effect of errors in the Doppler measurement. It will also be recognised that the accuracy of such an estimate of the speed will be highly dependent on the direction of heading of the user relative to the direction of the satellite. However, it is stressed that this estimation is not the final estimation of the speed of the receiver. Rather, it is part of a means of deciding which measurements are likely to have been derived from reflected signals, so that such measurements can be excluded from the subsequent, final, estimation of the receiver's position and velocity.
The process then passes to step 152, in which each of these individual estimates of the vehicle speed is examined to determine whether or not it is consistent with the satellite signal having been reflected. For example, this may simply involve determining whether or not the speed estimate is negative. That is, the speed estimate is compared with the direction of motion obtained in step 148. If it is found that the speed estimate derived from the Doppler measurement has a component towards the satellite vehicle when the direction of motion found in step 148 has a component away from the satellite vehicle (or vice versa), it is determined that that measurement is likely to have been derived from a reflected signal.
More generally, the examination of each individual estimate of the vehicle speed might involve comparing that estimate with a threshold.
Thus, the test is whether
S<x
S is the estimate of the vehicle speed obtained from a single Doppler measurement, based on a measured heading of the user relative to the direction of the satellite, and x is a threshold value.
In one example mentioned above, the threshold value x may be set to zero, such that the individual estimate of the vehicle speed is determined to be consistent with the satellite signal having been reflected when the speed estimate is negative.
In another example, the threshold value x may be set to a negative constant, such that the individual estimate of the vehicle speed is determined to be consistent with the satellite signal having been reflected when the speed estimate is more negative than that constant.
In a further example, the threshold value x may be set to the sum of a negative constant and a value representing the measurement uncertainty, such that the threshold is adapted based on the expected accuracy of the measurement.
As a further example, the threshold value x may be adapted to take account of the fact that, when the vehicle is moving with a heading that is close to perpendicular to its direction to the satellite, the estimate of the speed of the vehicle is likely to be of relatively poor quality. This can be used to set the threshold to alter (either increasing or decreasing) the likelihood that the estimate of the vehicle speed is determined to be consistent with the satellite signal having been reflected.
If it is found that the Doppler measurement derived from a particular signal is inconsistent with having been received along a direct path from the satellite (i.e. it is more consistent with having been received along a reflected path), then that particular Doppler measurement is flagged for rejection from all subsequent processing.
Specifically, the Doppler measurement is disregarded in the subsequent step 154, when computing the position and velocity of the vehicle, and possibly also computing the time (i.e. the components of the PVT solution). The computing step is generally conventional, and combines measurements obtained from multiple received signals in order to arrive at an estimate of the position and/or speed of the vehicle, but disregards the measurements obtained from a signal that is determined likely to have been reflected.
In addition, the pseudorange measurement obtained from the same signal may also be disregarded. Further, the positioning engine may instruct the measurement engine to cease tracking that signal, so no further measurements are derived from the reflected signal.
Thus, a reflection-focused outlier rejection process is executed. It is known to reject outlier measurements when computing a PVT solution using GNSS measurements as well as sensor inputs, etc. This known process typically considers a group of measurements received at one time, and assumes that only a small proportion of these measurements will be in error. It therefore assumes that an erroneous measurement can be recognised by being inconsistent with the other measurements. In the outlier rejection process described here, each GNSS measurement is considered in isolation from the other GNSS measurements, to determine whether it is consistent with information obtained from other sources, in particular from a heading sensor. If the measurement passes this test, it is then used in the computation of the PVT solution, it being recognised that this computation may include further outlier rejection steps.
The process shown in
There is thus described a process that allows the position and/or velocity of a user to be determined with greater precision, in particular in the case of a vehicle in an environment in which GNSS signals are highly prone to the effects of reflection from buildings etc.
| Number | Date | Country | Kind |
|---|---|---|---|
| 13 173 075.6 | Jun 2013 | EP | regional |
