TW201445163A - Positioning modules, positioning devices and methods for satellite positioning thereof - Google Patents

Abstract

A positioning module includes a satellite selecting module selecting a positioning satellite from satellites of satellite navigation systems and outputting a frequency information and a pseudo range of the positioning satellite, and a Kalman filter coupled to the satellite selecting module receiving the frequency information and the pseudo range of the positioning satellite and calculating a positioning information of the positioning module basing on the Kalman filtering algorithm.

Description

Positioning module, positioning device and satellite positioning method

The invention relates to the field of satellite navigation technology, in particular to a positioning module, a positioning device and a satellite positioning method.

The BD Navigation Satellite System is a self-developed, independently operated global satellite navigation system being implemented in China, with the US Global Positioning System (GPS) and the Russian Glonass satellite. The navigation system and the European Union's Galileo satellite navigation system are also known as the world's four major satellite navigation systems.

The existing receiver can only support one type of satellite navigation system described above, that is, it can only perform positioning based on the satellite signals of the same satellite navigation system received, and a receiver capable of supporting two or more satellite navigation systems has not been realized.

The invention provides a positioning module, comprising: a satellite selection module, selecting a positioning satellite from a plurality of satellites of a plurality of satellite navigation systems, and outputting a frequency information and a pseudorange of the positioning satellite; and a Karl The Manchester filter is coupled to the satellite selection module, receives the frequency information of the positioning satellite and the pseudorange, and calculates a positioning information of the positioning module based on a Kalman filter algorithm.

The present invention also provides a positioning apparatus comprising: a radio frequency module, mixing a received satellite signal with a local carrier signal to generate an intermediate frequency signal, wherein the satellite signal is from a plurality of satellite navigation systems a satellite; a baseband signal processing module that processes the received intermediate frequency signal to calculate a frequency information of the satellite and a pseudorange and receives the received signal The satellite signal is classified; and a positioning module is coupled to the baseband signal processing module, and selects a positioning satellite from the plurality of satellites according to the classification of the satellite signal, and according to the selected frequency information of the positioning satellite and The pseudorange calculates a positioning information of the positioning device based on a Kalman filter algorithm.

The invention also provides a satellite positioning method, comprising: receiving a satellite signal, wherein the satellite signal is from a satellite of a plurality of satellite navigation systems; obtaining a frequency of the satellite by capturing and tracking the satellite signal Information and a pseudorange and a classification of the satellite signal; selecting a positioning satellite from the plurality of satellites according to the classification of the satellite; and based on a frequency information and a pseudorange of the positioning satellite, based on a Kalman The filtering algorithm calculates a positioning information of a positioning device.

The positioning module, the positioning device and the satellite positioning method provided by the invention are based on the Kalman filter algorithm for positioning and solving in the satellite navigation system, which not only realizes support for a plurality of satellite navigation systems, but also improves positioning accuracy.

S10-S20‧‧‧Steps

S11-S17‧‧‧Steps

S171-S174‧‧‧Steps

10‧‧‧Test module

20‧‧‧Computation Module

21‧‧‧Distribution unit

22‧‧‧ Capture Tracking Unit

23‧‧‧Computation unit

500‧‧‧Second acquisition unit

502‧‧‧ satellite navigation system

5021-502J‧‧‧ Satellite

504‧‧‧Satellite navigation system

5041-504K‧‧‧ Satellite

506‧‧‧Antenna

508‧‧‧RF Module

510‧‧‧Baseband signal processing module

512‧‧‧ Positioning Module

514‧‧‧User Application Module

602‧‧‧ satellite selection module

604‧‧‧ Kalman filter

612‧‧‧Initial state calculation module

614‧‧‧Kalman Filter Computing Module

702-714‧‧‧Steps

702-714‧‧‧Steps

802-808‧‧‧Steps

910‧‧‧Track

920‧‧‧Track

The technical method of the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments to make the features and advantages of the present invention more obvious. Wherein: FIG. 1 is a flow chart of a satellite positioning method according to an embodiment of the invention.

2 is a flow chart showing a satellite positioning method according to another embodiment of the present invention.

3 is a flow chart of the dual mode satellite positioning method of FIG. 2, in accordance with an embodiment of the present invention.

FIG. 4 is a schematic structural diagram of a receiver according to an embodiment of the present invention.

FIG. 5 is a schematic structural view of a positioning device according to an embodiment of the invention.

FIG. 6 is a schematic structural diagram of a positioning module in a positioning device according to an embodiment of the invention.

FIG. 7 is a flow chart showing a method for positioning based on a Kalman filter algorithm in a navigation and positioning system according to an embodiment of the invention.

FIG. 8 is a flow chart showing a satellite positioning method according to an embodiment of the present invention.

Figure 9 shows a Kalman filter algorithm based on a single global positioning system navigation system with dual A schematic diagram of the trajectory comparison of the navigation system hybrid positioning.

A detailed description of the embodiments of the present invention will be given below. While the invention will be described in conjunction with the embodiments, it is understood that the invention is not limited to the embodiments. Rather, the invention is to cover various modifications, equivalents, and equivalents of the invention as defined by the scope of the appended claims.

In addition, in the following detailed description of the embodiments of the invention However, it will be understood by those of ordinary skill in the art that the present invention may be practiced without these specific details. In other instances, well-known methods, procedures, components, and circuits have not been described in detail in order to facilitate the invention.

The satellite navigation system of the embodiment of the invention includes a Beidou satellite navigation system, a global positioning system, a GLONAS satellite navigation system, and a Galileo satellite navigation system. Each satellite navigation system includes several satellites. In the embodiment of the present invention, a satellite capable of receiving a satellite signal by a receiver is referred to as a positioning satellite. Taking the Beidou satellite navigation system as an example, the Beidou satellite navigation system includes nine Beidou satellites. In the 2020 plan, the Beidou satellite navigation system will have 30 available satellites. If the receiver can receive the Beidou satellite signals of the six Beidou satellites, the six Beidou satellites are called Beidou positioning satellites.

FIG. 1 is a flow chart of a satellite positioning method according to an embodiment of the invention.

In step S10, it is detected whether the satellite signals received by the receiver are from different n satellite navigation systems, where n is an integer greater than one.

In step S20, if satellite signals from more than one satellite navigation system are received, the positioning information of the receiver and the receiver are compared with each satellite navigation system according to the satellite information of the positioning satellites in the navigation system corresponding to each satellite signal. The amount of displacement corresponding to the clock deviation.

The satellite information of the positioning satellite may specifically include pseudo-distance, coordinate information, frequency information, Doppler, ephemeris and speed information of the positioning satellite. The positioning information of the receiver may specifically include location information and speed information.

FIG. 2 is a flowchart of a satellite positioning method according to another embodiment of the present invention. The embodiment is described by taking a satellite signal of a Beidou satellite navigation system and a satellite signal of a global positioning system as an example, that is, a receiver. Received GPS satellite signals and Beidou satellite signals.

In step S11, it is judged whether or not the global positioning system satellite signal is received, if yes, step S12 is performed, otherwise step S13 is performed.

In step S12, it is determined whether the Beidou satellite signal is received, if yes, step S17 is performed, otherwise step S15 is performed.

In step S13, it is determined whether the Beidou satellite signal is received, if yes, step S16 is performed, otherwise step S14 is performed.

In step S14, the positioning cannot be achieved, and it is continuously detected whether or not the global positioning system satellite signal is received.

In step S15, the receiver is positioned using the global positioning system satellite signal.

In step S16, the receiver is positioned using the Beidou satellite signal.

In step S17, the receiver is positioned using the global positioning system satellite signal and the Beidou satellite signal.

In the above steps, an example of determining whether or not the global positioning system satellite signal is received is described. In fact, the order of judging whether a certain satellite signal is received is not limited thereto, and those skilled in the art can understand that it is also possible to first determine whether the received signal is a Beidou satellite signal, and also determine the received satellite first. Whether the signal is a Galileo satellite signal or a Girona satellite signal.

Since the Beidou satellite signal, the global positioning system satellite signal, and the Galileo satellite signal are all based on Code Division Multiple Access (CDMA) technology, the receiver can pass through the I branch in steps S11, S12, and S13. The ranging code identifies whether the received satellite signal is a Beidou satellite signal or a global positioning system satellite signal, and the Galileo satellite signal can also be identified through the I branch normal ranging code. Because the GLONAS satellite signal is based on Frequency Division Multiple Access (FDMA) Technology, the receiver can identify whether it is a Girona satellite signal through frequency. Therefore, satellite navigation systems can be distinguished by frequency information, and satellites in satellite navigation systems can be distinguished by code information.

Specifically, the equations representing the Beidou satellite signal and the global positioning system satellite signal are as follows: S ^j = AC ^j D ^j cos(2 πf t + θ ^j )

This equation also applies to Galileo satellite signals. Where A denotes the amplitude of the ordinary ranging code modulated in the I branch; C denotes the ordinary ranging code of the I branch; D denotes the navigation message data on the I branch; f denotes the carrier frequency of the satellite signal; t denotes the emission of the satellite signal Time; j represents the ID of the satellite; S ^j represents the signal transmitted by the satellite with satellite ID j; θ represents the initial carrier phase of each satellite signal, and the θ values of the respective satellites may be different. On the satellite side, each parameter in this equation is known; on the receiver side, each parameter needs to be known through signal acquisition and tracking. In addition, the f values of different satellite navigation systems are different, but since the Beidou satellite signal, the global positioning system satellite signal and the Galileo satellite signal are all based on code division multiple access technology, the transmission frequency of the same signal segment in the three systems is the same. . The Girona satellite signal is based on frequency division multiple access technology, so the satellites in the GLONAS satellite navigation system are distinguished by different transmission frequencies.

Each Beidou satellite, Global Positioning System satellite, and Galileo satellite has a unique pseudo-random number (PRN) generation rule, so it can be pseudo-random number order (equation S ^j = AC ^j D ^j cos (2) C) in πf t + θ ^j ) identifies which satellite signal is specifically. For the receiver, the pseudo-random number sequence of the reconstructed satellite can be used to search for and identify the currently available satellite signals. The reconstruction process is specifically as follows: the pseudo-random number order generation rule method is published through the interface control document (ICD) of each satellite navigation system, therefore, the receiver needs to search for possible satellite receiving frequency and pseudo-random number information. After receiving the satellite signal of one satellite, the navigation message data D and the carrier phase θ of the I branch can be obtained, and the baseband channel generates a pseudo-random number sequence consistent with the satellite, and attempts to capture the satellite and track. If the acquisition tracking is successful, it indicates that the satellite signal is present in the current input signal. In addition, the correlation peak appears in the code division multiple access only when the pseudo-random number reconstructed locally is consistent with the pseudo-random number of the input signal. Therefore, the correlation peak of the code division multiple access can be detected by setting the corresponding capture threshold to Determine if the capture is successful.

Satellites typically broadcast two ranging codes, which are respectively loaded on the I and Q branches of the satellite signal. Taking the Beidou satellite navigation system as an example, the I branch is a civilian common ranging code; the Q branch is a professional area (for example, military) precision ranging code, which needs to be authorized and the receiver can receive.

For step S15 and step S16, when only satellite signals of one satellite navigation system are received, for example, only the Beidou satellite signal is received, the receiver determines its position information by the following equations (1-1) to (1-n) The amount of displacement corresponding to the clock deviation of the Beidou satellite navigation system.

Where ρ ₁ ~ ρ _n respectively represent the pseudoranges of n Beidou positioning satellites, which can be measured through the tracking loop; ( x _i , y _i , z _i ) represent the coordinate information of each Beidou positioning satellite at the time of positioning, where 1 i n , coordinate information can be calculated by the orbital parameters and positioning time of the positioning satellite, and the orbital parameter is after demodulating the navigation message data D on the I branch after the satellite signal tracking and locking, and according to the interface control file of the satellite navigation system And collected. In addition, ( x _i , y _i , z _i ) is the coordinate in the ECEF coordinate system. The ECEF coordinate is based on the Earth's centroid, the Z axis is northward along the Earth's rotation axis, and the X axis is pointing to the latitude and longitude (0,0). Position, the Y-axis of the right hand is pointing to the 90-degree warp; b _u is the displacement corresponding to the clock deviation of the Beidou satellite navigation system; ( x _u , y _u , z _u ) is the position information of the receiver. Therefore, there are four unknowns ( x _u , y _u , z _u ) and b _u , and at least four positioning satellite parameters are needed to perform the positioning solution.

FIG. 3 is a flow chart showing a method for positioning a dual mode satellite according to an embodiment of the present invention, that is, a method for positioning a receiver through a Beidou satellite signal and a global positioning system satellite signal in step S17 of FIG.

In step S171, the receiver allocates resources for the positioning satellite.

In this step, the receiver is based on the positioning satellite that receives the satellite signal. Resources such as visibility, performance, and the environment in which they are located. Resources include hardware acquisition channels, tracking channels, etc., as well as software for central processing system resources.

The receiver judges the visibility based on the ephemeris of the positioning satellite receiving the signal, that is, whether the positioning satellite is above or below the line of sight of the receiver, and if it is above the line of sight of the receiver, Allocate resources, if you are under the line of sight, do not allocate resources or allocate resources less. In addition, for various satellite signals, because of their different encoding formats, the time taken to scan them is different. If the scanning time is too long, the positioning efficiency is lowered. These are all factors that are considered by the receiver.

In step S172, the receiver performs tracking and capture on the positioning satellites allocated with resources to obtain satellite information of each positioning satellite, including pseudorange, coordinate information, speed information and frequency information.

In this step, since the pseudorange measurement of the satellite may have a certain error, increasing the number of satellites participating in the positioning can reduce the influence of other satellite measurement errors on the positioning result, that is, improve the positioning accuracy, when the satellite error is equivalent. Considering many factors such as the amount of calculation, the number of satellites participating in positioning is generally limited to 12.

In step S174, the receiver calculates the position information, the speed information of the receiver, and the displacement amount corresponding to the clock deviation of the receiver with respect to each satellite navigation system based on the satellite information obtained in step S172.

For step S174, the receiver calculates its position information and displacement by the following equation: in the case where the receiver can receive satellite signals of k satellite navigation systems:

Where ρ ₁₁ ~ ρ _{1 m} respectively represent pseudoranges of m positioning satellites of the first satellite navigation system; ρ ₂₁ ~ ρ _{2 n} respectively represent pseudoranges of n positioning satellites of the second satellite navigation system; ρ _{k 1} ~ ρ _kp denotes the pseudorange of p positioning satellites of the kth satellite navigation system, respectively, k is an integer greater than or equal to 1, wherein the pseudorange can be measured through the tracking loop; ( x _{1 i} , y _{1 i} , z _{1 i} ) indicates coordinate information of each positioning satellite of the first satellite navigation system at the time of positioning, where 1 i m ;(x _{2 j} , y _{2 j} , z _{2 j} ) represents coordinate information of each positioning satellite of the second satellite navigation system at the time of positioning, wherein 1 j n ; ( x _ko , y _ko , z _ko ) represents coordinate information of each positioning satellite of the kth satellite navigation system at the time of positioning, where 1 o p , each coordinate information can be calculated through the orbital parameters and positioning time of the corresponding positioning satellite, and 1 m + n + p 12; b _{u 1} represents the displacement amount corresponding to the clock deviation of the receiver relative to the first satellite navigation system, that is, the displacement amount corresponding to the clock deviation of the local clock relative to the clock of the satellite navigation system; b _{u 2} indicates reception The amount of displacement corresponding to the clock deviation of the second satellite navigation system; b _uk represents the displacement corresponding to the clock deviation of the receiver relative to the kth satellite navigation system; ( x _u , y _u , z _u ) indicates reception Machine location information.

Since the present embodiment is described by taking satellite signals from two satellite navigation systems as an example, the Beidou satellite signal and the global positioning system satellite signal are received. Therefore, in the above equation, k=2, only the equations (2-11) to (2-2n) are needed to calculate the position information of the receiver. In this case, there are five unknowns ( x _u , y _u , z _u ), b _{u 1} and b _{u 2} , and at least five positioning satellite parameters are required to perform the positioning solution.

It can be seen that when receiving satellite signals from two satellite navigation systems, it is necessary to correspond to the clock deviation of the satellite navigation system relative to the receiver when compared to receiving satellite signals from a satellite navigation system. The displacement amount is corrected for the calculated positioning information to improve the positioning accuracy. And so on, when the receiver receives satellite signals from three or more satellite navigation systems, it is necessary to increase the corresponding satellite navigation system relative to The displacement amount corresponding to the clock deviation of the receiver is used to calculate the position information of the receiver. Moreover, the method provided by the embodiment can not only support the Beidou satellite navigation system and the global positioning system, but also support the GLONAS satellite navigation system and the Galileo satellite navigation system, that is, can support any one of the above satellite navigation systems or Multiple.

In summary, the above equations (2-11) to (2-kp) can also be expressed by the following equation (2):

Where ρ _ij represents the pseudorange of the jth positioning satellite of the i-th satellite navigation system; b _ui represents the displacement corresponding to the clock deviation of the receiver relative to the i-th satellite navigation system; ( x _ij , y _ij , z _ij ) indicates coordinate information of the jth positioning satellite of the i-th satellite navigation system at the time of positioning; ( x _u , y _u , z _u ) indicates position information of the receiver at the time of positioning.

In addition, because in some areas, some satellite navigation systems have fewer satellites available for positioning, so if only one satellite signal is used for positioning, the positioning accuracy will be reduced. If the receiver can support multiple satellite navigation systems, the number of satellites available for positioning will increase a lot, so the positioning or speed measurement accuracy will be greatly improved.

On the other hand, in step S174, the speed information of the receiver is calculated according to the following equation:

Where f _ij represents the receiving frequency of the j-th positioning satellite of the i-th satellite navigation system by the receiver; f _Tij represents the transmission frequency of the j-th positioning satellite of the i-th satellite navigation system, and for the satellite in the same satellite navigation system, it can be considered The transmission frequency is the same. For example, the Beidou satellite's B1 signal transmission frequency is 1.561098e9 Hz, and the global positioning system satellite's L1 signal has a transmission frequency of 1.57542e9 Hz. Therefore, if the i-th satellite navigation system includes three satellites, then f _{T 11} = f _{T 12} = f _{T 13} , in this embodiment, the receiving frequency and the transmitting frequency are referred to as frequency information; c is the speed of light, which is 2.97972458e8 meters/second; ( v _{ij_x} , v _{ij_y} , v _{ij_z} ) respectively The speed information of the jth positioning satellite of the i-th satellite navigation system at the time of positioning can be calculated through the ephemeris and current time of the satellite; ( a _{ij_x} , a _{ij_y} , a _{ij_z} ) respectively represent the j-th positioning of the i-th satellite navigation system The direction vector of the satellite relative to the receiver, and a _{ij_x} = ( x _ij - x _u ) / r , a _{ij_y} = ( y _ij - y _u ) / r , a _{ij_z} = ( z _ij - z _u ) / r , where , r is the receiver relative to the ith satellite The distance of the jth positioning satellite of the navigation system; ( x _ij , y _ij , z _ij ) is the position information of the jth positioning satellite of the i-th satellite navigation system at the positioning moment; ( x _u , y _u , z _u ) is the reception Position information of the machine at the time of positioning; ( , , ) is the speed information of the receiver; For the local clock change rate of the receiver to be solved, ie the clock change speed of the receiver, assuming that the clock of the satellite navigation system is stable, the clock change rate is only related to the receiver's clock, which is the receiver. The first derivative of the clock deviation relative to the satellite navigation system.

After calculating the position information and speed information of the receiver through the above equation, the receiver can output the navigation track.

Further, between step S172 and step S174, step S173 (not shown in FIG. 3) may be further included. In step S173, each positioning satellite is identified according to the satellite information, and the positioning satellite whose quality does not meet the requirements is removed, that is, the satellite information of the positioning satellite whose tracking quality is not satisfactory is not used to calculate the positioning information of the receiver.

In the case that the pseudorange of the satellite and the measurement error of the Doppler are not large, increasing the number of satellites participating in the positioning can improve the accuracy of the positioning operation. However, if the tracking quality of the satellite is poor, that is, if the measurement error of the pseudorange and Doppler is large, increasing the satellite participating in the positioning will reduce the accuracy, and such a satellite will be considered not to meet the setting requirements, so it is necessary to The quality of the satellite is identified, and redundant satellites of poor quality are eliminated. The method for identifying a redundant satellite may include a Receiver Autonomous Integrity Monitoring (RAIM) method, or may be determined according to an output indicator of each receiver loop, for example, a variation of a carrier frequency and a pseudorange measurement value. The law of change, etc., but not limited to this.

FIG. 4 is a schematic structural diagram of a receiver according to an embodiment of the invention. As shown in FIG. 4, the receiver includes a detection module 10 and a calculation module 20.

The detection module 10 detects whether satellite signals of two or more satellite navigation systems are received. The computing module 20 is coupled to the detecting module 10, and when the detecting module 10 detects the satellite signals of two or more satellite navigation systems, it calculates and receives the satellite information according to each positioning satellite in each satellite navigation system. The positioning information of the machine and the displacement amount corresponding to the clock deviation of the receiver relative to each satellite navigation system.

Further, the computing module 20 in the embodiment of the present invention may include an allocating unit 21, an capturing and tracking unit 22, and a computing unit 23.

Among them, the allocating unit 21 allocates resources for the positioning satellites of the satellite navigation systems. The acquisition tracking unit 22 performs tracking acquisition on the positioning satellites to which resources are allocated by the distribution unit 21 to obtain satellite information of each positioning satellite. Satellite information may include pseudoranges, coordinate information, speed information, and frequency information. The calculation unit 23 calculates the positioning information of the receiver and the displacement amount corresponding to the clock deviation of the receiver with respect to each satellite navigation system based on the satellite information obtained by the acquisition tracking unit 22.

Specifically, the detecting module 10 of the embodiment of the present invention determines whether the satellite signal is a Beidou satellite signal, a global positioning system satellite signal, or a Galileo satellite signal according to the ordinary ranging code of the satellite signal I branch, and determines the satellite signal according to the frequency of the satellite signal. Whether it is the Girona satellite signal. The calculation unit 23 of the embodiment of the present invention calculates the position information of the receiver according to the above equations (2-11)-(2-kp), and calculates the speed information of the receiver according to the above equation (3).

In addition, the computing module 20 of the embodiment of the present invention may further include an identifying unit (not shown in FIG. 4), and screening the positioning satellites in each satellite navigation system according to the obtained satellite information, so as to make the tracking quality poor positioning. The satellite information of the satellite will not be used to calculate the positioning information of the receiver.

The satellite positioning method and receiver provided by the embodiments of the present invention identify the received satellite signals and acquire satellite information of each satellite navigation system corresponding to the satellite signals, and combine the time of the satellite navigation system with respect to the receiver. Positioning of the displacement corresponding to the pulse deviation not only supports the support of various satellite navigation systems, but also improves the positioning accuracy.

FIG. 5 is a schematic structural diagram of a positioning apparatus 500 of a multi-satellite navigation system according to an embodiment of the present invention. As shown in FIG. 5, the positioning device 500 (for example, a receiver) includes an antenna 506, a radio frequency module 508, a baseband signal processing module 510, a positioning module 512, and a user application module 514. In the embodiment shown in FIG. 5, positioning device 500 receives satellite signals from satellite navigation systems 502 and 504. Wherein the satellite navigation system (eg, Beidou satellite navigation system) 502 can include satellites 5021-502J (where J is greater than A positive integer of 1), the satellite navigation system (e.g., global positioning system) 504 can include satellites 5041-504K (where K is a positive integer greater than one). Although only satellite navigation systems 502 and 504 are shown in FIG. 5, it will be understood by those of ordinary skill in the art that embodiments of the present invention are not limited to two satellite navigation systems and may include more satellites. Navigation System.

In one embodiment, positioning device 500 receives satellite signals from a plurality of satellite navigation systems via antenna 506. For example, positioning device 500 receives satellite signals from satellites 5021-502J in satellite navigation system 502 and satellites 5041-504K in satellite navigation system 504. In the embodiment shown in FIG. 5, since the positioning device 500 receives satellite signals from a plurality of satellite navigation systems, the antenna 506 can be configured as a multi-mode antenna to receive satellite signals of different frequencies.

The radio frequency module 508 receives satellite signals from a plurality of satellite navigation systems through the antenna 506, and mixes the received satellite signals with a local carrier signal generated by the positioning device 500 to generate an intermediate frequency signal. The generated intermediate frequency signal is transmitted to the baseband signal processing module 510 through amplification and analog/digital conversion.

The baseband signal processing module 510 captures, tracks and decodes the received intermediate frequency signal, thereby obtaining the frequency information and pseudorange of the satellite, and realizing the classification of the satellite, that is, identifying the received satellite signal from a certain satellite positioning system. A satellite in the middle. The frequency information of the satellite is the frequency of the satellite received by the positioning device 500 at the current time. For satellite signals based on frequency division multiple access modulation navigation systems, the received satellite signals can be identified by frequency. For the satellite signal of the navigation system based on code division multiple access modulation, the received satellite signal can be identified by the I branch normal ranging code.

The positioning module 512 receives the frequency information and the pseudorange from the baseband signal processing module 510, and selects a suitable positioning satellite from the satellites 5021-502J and 5041-504K according to the classification and identification of the satellites in the baseband signal processing module 510. And calculating the positioning information of the positioning device 500 based on the Kalman filter algorithm according to the selected frequency information and pseudorange of the positioning satellite. Subsequently, the positioning information of the positioning device 500 is converted into a standard format of the NMEA (The National Marine Electronics Association), and is output to the user application module 514. Hereinafter, the positioning module 512 will be described in detail.

FIG. 6 is a schematic structural diagram of a positioning module 512 in a positioning device 500 according to an embodiment of the invention. Figure 6 will be described in conjunction with Figure 5. As shown in FIG. 6, the positioning module 512 includes a satellite selection module 602 and a Kalman filter 604. The satellite selection module 602 selects a positioning satellite from a plurality of satellites (for example, satellites 5021-502J and 5041-504K) to cause the positioning module 512 to perform positioning and output, and outputs frequency information and pseudorange of the selected positioning satellite. The Kalman filter 604 is coupled to the satellite selection module 602, receives the frequency information and pseudorange of the positioning satellite, and calculates the positioning information of the positioning device 500 based on the Kalman filter algorithm.

In one embodiment, the satellite selection module 602 selects the positioning satellite based on factors such as the signal strength of the satellite signal, the satellite elevation angle, and the tracking quality of the satellite. In operation, the satellite selection module 602 first determines whether the received satellite from a satellite navigation system (e.g., satellite navigation system 502) is sufficient to calculate positioning information for the positioning device 500. Specifically, the satellite selection module 602 determines whether the satellite in the satellite navigation system can be calculated according to the positioning device 500 according to satellite signal strength, satellite number, and precision attenuation (DOP) indicators in a single satellite navigation system. Location information. If the positioning device 500 can be accurately located using a satellite in a satellite navigation system (e.g., satellite navigation system 502), there is no need to select satellites in other satellite navigation systems; otherwise, selection from other satellite navigation systems is also required. A satellite in (e.g., satellite navigation system 504). For example, the satellite selection module 602 receives satellite signals from five satellites, four of which are satellites in the global positioning system, and one satellite is a satellite in the Beidou system. The satellite selection module 602 detects that the four global positioning system satellites have good signal strength and other parameters, and can achieve the required positioning of the positioning device 500, and consider that the positioning device 500 has different clock deviations with respect to different navigation systems. Adding satellite signals of another navigation system will increase an unknown number, so the satellite selection module 604 selects the four satellites from the global positioning system to perform single navigation system positioning on the positioning device 500. In another case, it is assumed that the satellite selection module 602 receives satellite signals of five satellites, three of which are global positioning system satellites and two of which are Beidou satellites. Although it is considered that the positioning device 500 has different clock deviations with respect to different navigation systems, the three global positioning system satellites are not sufficient to achieve positioning of the positioning device 500, in which case the satellite selection The selection module 602 selects three satellites from the global positioning system and two satellites from the Beidou system for positioning of the multi-navigation system to achieve precise positioning of the positioning device 500. In still another case, it is assumed that the satellite selection module 602 receives satellite signals of six satellites, four of which are global positioning system satellites, two of which are Beidou satellites, and the four global positioning system satellites have weak signal strength. . In this case, although the positioning of the positioning device 500 can be achieved by four satellites, the result of solving the satellite with weak signal strength may result in inaccurate positioning. Therefore, the satellite selection module 602 also selects four satellites from the global positioning system and two satellites from the Beidou system to perform positioning of the multi-navigation positioning system to improve positioning accuracy.

After selecting the positioning satellite, the satellite selection module 602 transmits the pseudorange and frequency information of the positioning satellite to the Kalman filter 604; the Kalman filter 604 performs the positioning solution based on the Kalman filtering algorithm. As shown in FIG. 6, the Kalman filter 604 includes an initial state calculation module 612 and a Kalman filter calculation module 614. In the following, the Kalman filter 604 in the positioning module will be described in detail in conjunction with the flowchart of the Kalman filter algorithm.

FIG. 7 is a flow chart showing positioning based on a Kalman filter algorithm in a navigation and positioning system according to an embodiment of the present invention. Figure 7 will be described in conjunction with Figure 6.

For positioning devices, there are three general Kalman models: P model, PV model and PVA model. In the P model, the position state is considered to be random walk, which is often used in static scenes; in the PV model, the velocity is considered to be random walk, generally used in low dynamic motion environments; in the PVA model, the state vector needs to be increased. The three acceleration components, the acceleration is considered to be random walk, and are generally used in scenes where the range of motion acceleration of the positioning device varies greatly, for example, a high-speed aircraft. In the following, a state equation will be established taking the PV models of M navigation systems as an example, where M is a positive integer greater than or equal to 1. It should be understood by those of ordinary skill in the art that state equations and observation equations based on the Kalman filter algorithm can also be established in the P model and the PVA model.

In the Kalman filter algorithm, the equation of state is defined as: X _{k +1} = Φ _k X _k + w _k (4-1)

Where X is a state vector; Φ is a state matrix; w is a state noise; K is an integer greater than or equal to 1.

The observation equation is defined as: Z _k = H _k X _k + v _k (4-2)

Where Z is the observation vector; H is the measurement matrix; and v is the measurement noise.

For M navigation systems, define the state vector X = [p _x , p _y , p _z , v _x , v _y , v _z , b _u1 , b _u2 ,...b _uM ,c Wherein, p _x , p _y , p _z represent the position of the positioning device 500 under the ECEF coordinate system; v _x , v _y , v _z represent the speed of the positioning device 500 under the ECEF coordinate system; b _u1 , b _u2 , ...b _uM denotes the clock deviation of the local time system of the positioning device 500 with respect to the navigation systems 1, 2, ..., M; Indicates the clock drift of the local time system; c represents the speed of light, where M represents the number of navigation systems participating in the positioning. Therefore, the length of the state vector is (7+M). For example, when there are two navigation systems involved in positioning, the length of the state vector is 9, that is, the state vector is X=[p _x , p _y , p _z , v _x , v _y , v _z , b _u1 , b _u2 ,c ].

Therefore, for M navigation systems, the equation of state can be expressed as (4-3):

Wherein the position p represents the positioning device 500 in the ECEF coordinate system _{(p x, p y, p} z); v represents the speed of the positioning device 500 in the ECEF coordinate system _{(v x, v y, v} z); t u Indicates the clock skew of the local time system and each navigation system (b _u1 , b _u2 , ... b _uM ); Indicates the clock drift of the local time system.

Therefore, for M navigation systems, the state matrix Φ is a (7+M)×(7+M) order matrix:

For example, for a dual navigation system, the state matrix Φ is 9×9 steps: Where T is the positioning period of the positioning device.

According to the foregoing description, in the M navigation systems, the position observation equation can be expressed by (4-11)-(4-Mp):

Where ρ ₁₁ ~ ρ _{1 m} respectively represent pseudoranges of m positioning satellites of the first satellite navigation system; ρ _{M 1} ~ ρ _Mp respectively represent pseudoranges of p positioning satellites of the M satellite navigation system, and the pseudoranges can Obtained by the tracking loop, where M is an integer greater than or equal to 1; ( x _{1 i} , y _{1 i} , z _{1 i} ) represents coordinate information of each positioning satellite of the first satellite navigation system at the time of positioning, where 1 i m ;( x _Mo , y _Mo , z _Mo ) represents the coordinate information of each positioning satellite of the M satellite navigation system at the time of positioning, where 1 o p , each coordinate information can be calculated through the orbital parameters and positioning time of the corresponding positioning satellite, and m +...+ p = N (N is the number of positioning satellites participating in the positioning); b _{u 1} indicates that the positioning device 500 is opposite The clock deviation of the first satellite navigation system, that is, the deviation of the local clock from the clock of the satellite navigation system; b _uM represents the clock deviation of the positioning device 500 relative to the M satellite navigation system; ( x _u , y _u , z _u ) represents the position information of the positioning device 500.

In addition, for M navigation systems, if there are N satellites participating in the positioning, the equation of observation of velocity is expressed as: d = Hg (5-1)

Where d represents the component of the speed of the positioning device 500 on the vector of the positioning device 500 to the positioning satellite, ie:

According to the above equations (4-11)-(4-Mp) and (5-1), the observation vector Z can be obtained: Z = [ ρ ₁₁ , ... ρ _1m , ... ρ _M1 , ... ρ _Mp ,d ₁₁ , ... d _1m ,... d _M1 ,... d _Mp ] ^T , where m represents the number of positioning satellites participating in the positioning in the first navigation system; p represents the positioning satellites participating in the positioning in the M navigation system ρ denotes the pseudorange participating in the positioning satellite; d denotes the component of the speed of the positioning device 500 on the vector of the positioning device 500 to the satellite, in units of meters per second. The length of the observation vector Z is 2 × (m + ... + p).

Thus, the measurement matrix of the M navigation systems based on the Kalman filter algorithm can be expressed as a (2N)×(7+M) order matrix. N is the number of positioning satellites participating in the positioning, and N=m+...+p, where m is the number of positioning satellites participating in the positioning in the first navigation system, and p is the number of positioning satellites participating in the positioning in the M navigation system. M is the number of navigation systems involved in positioning. Taking the measurement matrix of the dual navigation system as an example, assuming that there are m positioning satellites participating in the positioning in the first satellite navigation system and p satellites participating in the positioning in the second satellite navigation system, the measurement matrix is (2×(m+p) ) × 9-order matrix:

among them, , A indicates the navigation system participating in the positioning, taking the dual navigation system as an example, A is equal to 1 or 2; An x component representing an estimated value of the position of the positioning device 500 under the ECEF coordinate system; X _j representing an x component of the position of the positioning satellite under the ECEF coordinate system; Represents the estimated distance from the positioning satellite to the positioning device 500.

It should be understood that the element positions of the state vector X can be exchanged arbitrarily, and the corresponding state matrix and measurement matrix need to be adjusted after the exchange. Similarly, the position of the elements in the observation vector Z can also be exchanged arbitrarily, and the corresponding state matrix and measurement matrix need to be adjusted after the exchange.

As shown in FIG. 7, in step 702, the Kalman filter 604 in the initial state calculation module 612 calculates the Kalman filter 604 of the initial state vector X ₀ and initial error covariance P _0. When the initialization is completed, step 704 is performed, otherwise step 703 is performed.

In step 703, the Kalman filter is generally initialized using a least squares method. Wave 604.

In step 704, the Kalman filter calculation module 614 determines the observation vector Z of the Kalman filter 604 at the current time. As described above, the observation vector Z includes the pseudorange of the positioning satellite participating in the positioning and the component of the speed of the positioning device on the vector of the positioning device to the positioning satellite. That is, Z = [ ρ ₁₁ , ... ρ _1m , ... ρ _M1 , ... ρ _Mp , d ₁₁ , ... d _1m ,... d _M1 ,... d _Mp ] ^T , the length of the observation vector Z 2 × N, N represents the number of positioning satellites participating in the positioning, and N = m + ... + p. Wherein m represents the number of positioning satellites participating in the positioning in the first navigation system; p represents the number of positioning satellites participating in the positioning in the M navigation system; and M represents the number of navigation systems participating in the positioning.

In step 705, an initial state vector X ₀ and an initial error covariance P _{0 are obtained} .

In step 706, the Kalman filter calculation module 614 calculates an estimated value of the state vector of the current time k based on the state vector of the previous time k-1. In one embodiment, the Kalman filter calculation module 614 (6-1) equation is calculated based on the estimated current value of the state vector at time k ^{_{X - k: X - k =}} Φ k X k-1 (6-1)

In step 708, the Kalman filter calculation module 614 calculates an estimate of the error covariance at the current time k based on the error covariance of the previous time k-1. In one embodiment, the Kalman filter calculation module 614 calculates a current estimated value of the error covariance P at time k according to equation _{^{(6-2) - k: P -}} k = Φ k P k-1 Φ k T + Q _k (6-2)

Where Q _k represents the process excitation noise covariance.

In step 710, the Kalman filter calculation module 614 calculates the Kalman gain K _{k of the} current time according to the estimated value P ^- _{k of the} calculated error covariance according to the equation (6-3): K _k = P ^- _k H _k ^T [H _k P _k ^- H _k ^T +P _k ] ^-1 (6-3)

In step 712, the Kalman filter calculation module 614 updates according to the calculated Kalman gain K _k , the estimated value of the state vector of the current time X ^- _{k ,} and the observation vector Z of the current time according to equation (6-4). State vector of the current moment X _k : X _k =X ^- _k +K _k [Z _k -H _k X _k ^- ] (6-4)

In step 714, the Kalman filter calculation module 614 updates the error covariance of the current time according to the equation (6-5) according to the calculated Kalman gain K _k and the estimated value P ^- _k of the error covariance at the current time. P _k :P _k =[1-K _k H _k ]P _k ^- (6-5)

The state vector X _k of the current time obtained by the update may be output to the user application module 514 after being verified as valid. Further, at the next time (k + 1), the state vector X _k and error covariance after updating time k P _k obtained can be used as the value of the previous time (k + 1) time to update the (k + 1 The state vector X _(k+1) and the error covariance P _(k+1) at the moment. This updated step repeats steps 704-714 and will not be described in detail herein.

FIG. 8 is a flow chart showing a satellite positioning method according to an embodiment of the present invention. Figure 8 will be described in conjunction with Figures 5 and 6.

In step 802, positioning device 500 receives satellite signals from a plurality of navigation systems. More specifically, as shown in FIG. 5, positioning device 500 receives satellite signals from satellites 5021-502J and 5041-504K in navigation systems 502 and 504 via antenna 506.

In step 804, the positioning device 500 calculates the frequency and pseudorange of the satellite signal and obtains classification information of the satellite signal. More specifically, the radio frequency module 508 in the positioning device 500 mixes the received satellite signal with a local carrier signal generated by the positioning device 500 to generate an intermediate frequency signal. The generated intermediate frequency signal is transmitted to the baseband signal processing module 510 through amplification and analog/digital conversion. The baseband signal processing module 510 captures, tracks, and decodes the received intermediate frequency signal, thereby obtaining frequency information and pseudorange of the satellite signal and realizing classification of the satellite signal. For example, the baseband signal processing module 510 in the positioning device 500 can transmit a pseudo-random number sequence signal of the local reconstructed satellite to identify which navigation system the received satellite signal is from.

In step 806, the positioning device 500 selects a positioning satellite from satellites (eg, satellites 5021-502J and 5041-504K) to calculate positioning information for the positioning device 500, such as location information and speed information for the positioning device. For example, the satellite selection module 602 in the positioning device 500 selects the positioning satellite based on factors such as the received signal strength of the satellite signal, the satellite elevation angle, and the tracking quality of the satellite.

In step 808, after the satellite selection module 602 selects the positioning satellite, the pseudorange and frequency information of the positioning satellite is output to the Kalman filter 604. The Kalman filter 604 calculates the positioning information of the positioning device 500 according to the Kalman filter algorithm based on the pseudorange and frequency information of the received positioning satellite.

Specifically, the initial state calculation module 612 in the Kalman filter 604 calculates the initial state vector X ₀ and the initial error covariance P _{0 of the} Kalman filter.

Upon completion of initialization, the Kalman filter calculation module 614 in the Kalman filter 604 determines the observation vector Z of the Kalman filter 604 at the current time.

Thereafter, the Kalman filter calculation module 614 calculates a current estimated value of the state vector of the state vector at time k in accordance with the previous time, and to calculate an estimate error covariance P k in accordance with the current time covariance a previous time ^- _k . After that, the Kalman filter calculation module 614 calculates the Kalman gain K _k at the current time based on the calculated estimated value P ^- _k of the error covariance. After calculating the Kalman gain K _k, the Kalman filter module 614 is calculated based on the estimated value of the state vector X on the calculated Kalman gain K _k, the current time ^- the current time and the observation vector _k of Z, updates the current time The state vector X _k , and the error covariance P _k at the current time is updated based on the calculated Kalman gain K _k and the estimated value P ^- _k of the error covariance at the current time. The state vector X _k of the current time obtained by the update may be output to the user application module 514 after being verified as valid.

Further, at the next time (k + 1), the state vector X _k and error covariance after updating time k P _k obtained can be used as the value of the previous time (k + 1) time to update the (k + 1 The state vector X _(k+1) and the error covariance P _(k+1) at the moment.

Figure 9 is a schematic diagram showing the trajectory comparison of the hybrid positioning of the single global positioning system navigation system and the dual navigation system with weak signal strength. As shown in FIG. 9, 910 denotes a trajectory obtained by using a Kalman filter algorithm in a single global positioning system navigation system with weak signal strength, and 920 denotes a trajectory obtained by using a Kalman filter algorithm in a hybrid positioning of a dual navigation system. It can be seen from FIG. 9 that for a single navigation system with weak signals, satellite signals from other navigation systems are selected, and the positioning of the multi-navigation system based on the Kalman filter algorithm can obtain relatively accurate positioning results.

The above detailed description and the accompanying drawings are only typical embodiments of the invention. It is apparent that various additions, modifications and substitutions are possible without departing from the spirit and scope of the invention as defined by the appended claims. It should be understood by those of ordinary skill in the art that the present invention may be applied in the form of the form, structure, arrangement, ratio, material, element, element, and other aspects in the actual application without departing from the invention. Changed. Therefore, the embodiments disclosed herein are intended to be illustrative and not restrictive, and the scope of the invention is defined by the scope of the appended claims

500‧‧‧Second acquisition unit

502‧‧‧ satellite navigation system

5021-502J‧‧‧ Satellite

504‧‧‧Satellite navigation system

5041-504K‧‧‧ Satellite

506‧‧‧Antenna

508‧‧‧RF Module

510‧‧‧Baseband signal processing module

512‧‧‧ Positioning Module

514‧‧‧User Application Module

Claims (20)

A positioning module includes: a satellite selection module, selecting a positioning satellite from a plurality of satellites of a plurality of satellite navigation systems, and outputting a frequency information and a pseudorange of the positioning satellite; and a Kalman filter, The satellite selection module is coupled to receive the frequency information of the positioning satellite and the pseudorange, and calculate a positioning information of the positioning module based on a Kalman filtering algorithm. The positioning module of claim 1, wherein the Kalman filter comprises: an initial state calculation module, and calculating an initial of the Kalman filter according to the frequency information of the positioning satellite and the pseudorange a state vector and an error covariance; and a Kalman filter calculation module, based on the Kalman filter algorithm, calculating a state vector of a current time, the state vector including the positioning information of the positioning module. The positioning module of claim 2, wherein the state vector comprises a position of the positioning module, a speed, a local time system and a clock deviation of the plurality of satellite navigation systems, and the local time system One clock drift. The positioning module of claim 2, wherein a length of the state vector is (7+M), wherein M is a number of the plurality of satellite navigation systems in which the positioning satellite is located. For example, the positioning module of claim 2, wherein the Kalman filter calculation module uses the Kalman filter algorithm to update the current state according to a state vector of a previous moment and an observation vector of the current moment. The state vector of the time, wherein the observation vector includes the pseudorange of the positioning satellite and the positioning A speed of the module is a component of the positioning module to a vector of the positioning satellite. For example, the positioning module of claim 5, wherein a length of the observation vector is 2×N, where N is a number of the positioning satellite. A positioning device includes: an RF module, mixing a received satellite signal with a local carrier signal to generate an intermediate frequency signal, wherein the satellite signal is from a satellite of a plurality of satellite navigation systems; a baseband a signal processing module, processing the received intermediate frequency signal to calculate a frequency information of the satellite and a pseudorange and classifying the received satellite signal; and a positioning module coupled to the baseband signal processing module And selecting a positioning satellite from the plurality of satellites according to the classification of the satellite signal, and calculating a positioning information of the positioning device based on a Kalman filtering algorithm according to a frequency information of the positioning satellite and a pseudorange. The positioning device of claim 7, wherein the positioning module comprises: a satellite selection module, selecting the positioning satellite from the plurality of satellites, and outputting the frequency information of the positioning satellite and the pseudorange; And a Kalman filter coupled to the satellite selection module, receiving the frequency information of the positioning satellite and the pseudorange, and calculating the positioning information of the positioning device based on the Kalman filter algorithm. The positioning device of claim 8 , wherein the Kalman filter comprises: an initial state calculation module, and calculating an initial state of the Kalman filter according to the frequency information of the positioning satellite and the pseudorange Vector and an error covariance a matrix; and a Kalman filter calculation module, based on the Kalman filter algorithm, calculating a state vector of a current time, the state vector including the positioning information of the positioning device. The positioning device of claim 9, wherein the state vector comprises a position of the positioning device, a speed, a local time system and a clock deviation of the plurality of satellite navigation systems, and a time of the local time system drift. The positioning device of claim 9, wherein the length of the state vector is (7+M), wherein M is a number of the plurality of satellite navigation systems in which the positioning satellite is located. The positioning device of claim 9, wherein the Kalman filter calculation module uses the Kalman filter algorithm to update the current time according to a state vector of a previous moment and an observation vector of the current moment. The state vector, wherein the observation vector includes the pseudorange of the positioning satellite and a component of the positioning device at a speed of the positioning device to a vector of the positioning satellite. The positioning device of claim 12, wherein a length of the observation vector is 2×N, where N is a number of the positioning satellite. A satellite positioning method includes: receiving a satellite signal, wherein the satellite signal is from a satellite of a plurality of satellite navigation systems; obtaining a frequency information and a pseudorange of the satellite through a capture and a tracking of the satellite signal And implementing a classification of the satellite signal; selecting a positioning satellite from the plurality of satellites according to the classification of the satellite signal; According to a frequency information of the positioning satellite and a pseudorange, a positioning information of a positioning device is calculated based on a Kalman filter algorithm. The satellite positioning method of claim 14, wherein the step of calculating the positioning information of the positioning device based on the Kalman filter algorithm according to the frequency information of the positioning satellite and the pseudorange comprises: determining a current time An observation vector of a Kalman filter, the observation vector comprising the pseudorange of the positioning satellite and a component of the positioning device at a speed of the positioning device to the positioning satellite; and according to a previous one Updating a state vector of the current time by a state vector of the time and the observation vector of the current time, wherein the state vector includes a position of the positioning device, the speed of the positioning device, and a local time of the positioning device A clock offset of the system from the plurality of satellite navigation systems, and a clock drift of the local time system. The satellite positioning method of claim 15, wherein the updating the state vector of the current time according to the state vector of the previous moment and the observation vector of the current moment comprises: according to the previous moment a state vector, calculating an estimated value of the state vector at the current time; calculating an estimated value of an error covariance at the current time according to an error covariance of the previous time; and the error covariance according to the current time The estimated value, a Kalman gain is calculated; and the state vector of the current time is updated according to the calculated Kalman gain, the estimated value of the state vector at the current time, and the observed vector of the current time. For example, the satellite positioning method of claim 16 of the patent scope, wherein, according to the positioning The frequency information of the satellite and the pseudorange, the step of calculating the positioning information of the positioning device based on the Kalman filter algorithm further comprises: calculating the estimated value of the error covariance according to the calculated Kalman gain and the current time , updating the error covariance of the current moment. The satellite positioning method of claim 15, wherein the method further comprises: calculating a state vector of a moment according to the obtained error covariance of the current moment and the state vector of the current moment. The satellite positioning method of claim 15, wherein the length of the observation vector is 2×N, wherein N is a number of the positioning satellite. The satellite positioning method of claim 15, wherein a length of the state vector of the current time is (7+M), wherein M is a number of the plurality of satellite navigation systems in which the positioning satellite is located.