A beidou directional system and method

Abstract

The application relates to the field of Beidou positioning technology, in particular to a Beidou orientation system and method, which comprises a central processing module, two Beidou baseband modules and two Beidou antennas arranged on a Beidou orientation device; the two Beidou baseband modules are connected with the two Beidou antennas in one-to-one correspondence respectively; the central processing module comprises an ARM service processing unit and a DSP algorithm processing unit; a communication connection is established between the ARM service processing unit and the DSP algorithm processing unit; the ARM service processing unit is connected with the two Beidou baseband modules respectively; by using the mode of an ARM core and a DSP core, the two core processing data are relatively independent, and synchronous concurrent processing of data receiving and sending and data algorithm can be realized; data interaction is carried out between the ARM service processing unit and the DSP algorithm processing unit through a shared memory mode, and efficient data processing can be realized.

Description

Technical Field

[0001] This invention relates to the field of BeiDou positioning technology, and in particular to a BeiDou orientation system and method. Background Technology

[0002] To quickly provide equipment with position and orientation data, the traditional approach in China is to use inertial navigation systems (INS) and gyroscopes for positioning and orientation. However, these methods suffer from drawbacks such as expensive equipment and increasing orientation errors over time. With the gradual improvement of my country's BeiDou Navigation Satellite System, high-precision navigation, positioning, and orientation applications, as a crucial component of the BeiDou industrialization, are leading the development and upgrading of numerous industries, particularly demonstrating advantages in deformation monitoring, precision agriculture, and military navigation. Therefore, a high-precision BeiDou orientation system and method are particularly needed. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a high-precision BeiDou orientation system and method.

[0004] To solve the above-mentioned technical problems, the first technical solution adopted by the present invention is as follows:

[0005] A BeiDou orientation system includes a central processing module, two BeiDou baseband modules, and two BeiDou antennas mounted on a BeiDou orientation device. The two BeiDou baseband modules are connected to the two BeiDou antennas in a one-to-one correspondence. The central processing module includes an ARM service processing unit and a DSP algorithm processing unit. The ARM service processing unit and the DSP algorithm processing unit establish a communication connection. The ARM service processing unit is connected to the two BeiDou baseband modules respectively.

[0006] The second technical solution adopted in this invention is:

[0007] A BeiDou orientation method, applied to the aforementioned BeiDou orientation system, includes the following steps:

[0008] S1. The Beidou baseband module sends ephemeris data and raw observation data to the ARM service processing unit;

[0009] S2. The ARM service processing unit receives the ephemeris data and raw observation data, and sends them to the DSP algorithm processing unit;

[0010] S3. The DSP algorithm processing unit receives the ephemeris data and the raw observation data, and performs calculations and processing based on the ephemeris data and the raw observation data to obtain the position data and direction data of the Beidou orientation device.

[0011] S4. The DSP algorithm processing unit sends the position data and direction data to the ARM service processing unit;

[0012] S5. The ARM service processing unit outputs the azimuth data, device status data, and version data of the Beidou orientation device based on the location data and direction data.

[0013] The beneficial effects of this invention are as follows:

[0014] This solution involves setting up a central processing module, two BeiDou baseband modules, and two BeiDou antennas on a BeiDou orientation device. The two BeiDou baseband modules are connected one-to-one with the two BeiDou antennas. The central processing module includes an ARM service processing unit and a DSP algorithm processing unit. The ARM service processing unit is connected to each of the two BeiDou baseband modules and receives data transmitted from them. A communication connection is established between the ARM service processing unit and the DSP algorithm processing unit. The ARM service processing unit transmits data to the DSP algorithm processing unit via shared memory. The DSP algorithm processing unit quickly solves and processes the transmitted data, and then calculates the solution. After receiving the direction data, it is then sent back to the ARM business processing unit. By using an ARM core + DSP core configuration, these two cores process data relatively independently, enabling true synchronous and concurrent processing of data transmission and reception and data algorithms. The ARM business processing unit and the DSP algorithm processing unit interact with each other through shared memory, enabling efficient data processing. The ARM core processes comprehensive business data, while the DSP algorithm processing unit utilizes its powerful digital signal processing capabilities to handle algorithmic tasks. This combination fully leverages the unique advantages of each core, maximizing the optimal performance of the central processing module and effectively improving the BeiDou orientation accuracy. Attached Figure Description

[0015] Figure 1 This is a connection block diagram of the Beidou orientation system of the present invention;

[0016] Figure 2 This is a circuit diagram of the central processing module of the Beidou orientation system of the present invention;

[0017] Figure 3 This is a circuit diagram of the BeiDou baseband module of the BeiDou orientation system of the present invention;

[0018] Figure 4 This is a structural diagram of the installation of the Beidou antenna in the Beidou orientation device of the Beidou orientation system of the present invention;

[0019] Figure 5 This is a circuit diagram of the debugging serial port unit of the Beidou orientation system of the present invention;

[0020] Figure 6 This is a circuit diagram of the TF card unit of the Beidou orientation system of the present invention;

[0021] Figure 7 The circuit diagram of the TL16C serial port expansion unit of the Beidou orientation system of the present invention is shown below.

[0022] Figure 8 This is a circuit diagram of the power supply unit of the Beidou orientation system of the present invention;

[0023] Figure 9 This is a flowchart of the BeiDou orientation method of the present invention;

[0024] Label Explanation:

[0025] 1. Beidou orientation device; 2. Central processing module; 3. Beidou baseband module; 4. Beidou antenna; 5. Debugging serial port unit; 6. TF card unit; 7. TL16C serial port expansion unit; 8. Power supply unit. Detailed Implementation

[0026] To explain in detail the technical content, objectives, and effects of the present invention, the following description is provided in conjunction with the embodiments and accompanying drawings.

[0027] Please refer to Figure 1 One technical solution adopted in this invention is as follows:

[0028] A BeiDou orientation system includes a central processing module, two BeiDou baseband modules, and two BeiDou antennas mounted on a BeiDou orientation device. The two BeiDou baseband modules are connected to the two BeiDou antennas in a one-to-one correspondence. The central processing module includes an ARM service processing unit and a DSP algorithm processing unit. The ARM service processing unit and the DSP algorithm processing unit establish a communication connection. The ARM service processing unit is connected to the two BeiDou baseband modules respectively.

[0029] As can be seen from the above description, the beneficial effects of the present invention are as follows:

[0030] This solution involves setting up a central processing module, two BeiDou baseband modules, and two BeiDou antennas on a BeiDou orientation device. The two BeiDou baseband modules are connected one-to-one with the two BeiDou antennas. The central processing module includes an ARM service processing unit and a DSP algorithm processing unit. The ARM service processing unit is connected to each of the two BeiDou baseband modules and receives data transmitted from them. A communication connection is established between the ARM service processing unit and the DSP algorithm processing unit. The ARM service processing unit transmits data to the DSP algorithm processing unit via shared memory. The DSP algorithm processing unit quickly solves and processes the transmitted data, and then calculates the solution. After receiving the direction data, it is then sent back to the ARM business processing unit. By using an ARM core + DSP core configuration, these two cores process data relatively independently, enabling true synchronous and concurrent processing of data transmission and reception and data algorithms. The ARM business processing unit and the DSP algorithm processing unit interact with each other through shared memory, enabling efficient data processing. The ARM core processes comprehensive business data, while the DSP algorithm processing unit utilizes its powerful digital signal processing capabilities to handle algorithmic tasks. This combination fully leverages the unique advantages of each core, maximizing the optimal performance of the central processing module and effectively improving the BeiDou orientation accuracy.

[0031] Furthermore, it also includes a debug serial port unit, which is connected to the central processing module.

[0032] As described above, by setting up a debug serial port unit and connecting it to the DSP algorithm processing unit, human-computer interaction can be achieved.

[0033] Furthermore, it also includes a TF card unit, which is connected to the central processing module.

[0034] As can be seen from the above description, by setting up a TF card unit, the TF card read and write functions can be realized.

[0035] Furthermore, it also includes a TL16C serial port expansion unit, which is connected to the central processing module.

[0036] As described above, serial port expansion can be achieved by setting up a TF card unit.

[0037] Please refer to Figure 9 Another technical solution provided by the present invention:

[0038] A BeiDou orientation method, applied to the aforementioned BeiDou orientation system, comprising the following steps:

[0039] S1. The Beidou baseband module sends ephemeris data and raw observation data to the ARM service processing unit;

[0040] S2. The ARM service processing unit receives the ephemeris data and raw observation data, and sends them to the DSP algorithm processing unit;

[0041] S3. The DSP algorithm processing unit receives the ephemeris data and the raw observation data, and performs calculations and processing based on the ephemeris data and the raw observation data to obtain the position data and direction data of the Beidou orientation device.

[0042] S4. The DSP algorithm processing unit sends the position data and direction data to the ARM service processing unit;

[0043] S5. The ARM service processing unit outputs the azimuth data, device status data, and version data of the Beidou orientation device based on the location data and direction data.

[0044] As can be seen from the above description, the beneficial effects of the present invention are as follows:

[0045] The BeiDou orientation method in this scheme sends ephemeris data and raw observation data to the ARM service processing unit via the BeiDou baseband module. The ARM service processing unit receives the ephemeris data and raw observation data and sends them to the DSP algorithm processing unit. The DSP algorithm processing unit receives the ephemeris data and raw observation data, and performs calculations and processing based on the ephemeris data and raw observation data to obtain the position data and orientation data of the BeiDou orientation device. The DSP algorithm processing unit sends the position data and orientation data to the ARM service processing unit. The ARM service processing unit outputs the azimuth data, device status data, and other information of the BeiDou orientation device based on the position data and orientation data. Version data enables high-precision positioning of BeiDou; by using an ARM core + DSP core mode, the two cores process data relatively independently, which can truly realize the synchronous and concurrent processing of data transmission and reception and data algorithms; the ARM business processing unit and the DSP algorithm processing unit interact with each other through shared memory, which can achieve efficient data processing; the ARM core processes comprehensive business data, while the DSP algorithm processing unit uses its powerful digital signal processing capabilities to handle algorithmic work. This combination fully utilizes the unique advantages of the two cores, maximizes the optimal efficiency of the central processing module, and thus effectively improves the orientation accuracy of BeiDou.

[0046] Furthermore, in step S3, the DSP algorithm processing unit performs a fuzzy search algorithm within the value range to solve the problem. The fuzzy search algorithm includes the following steps:

[0047] S31. Initialize the search step size and fuzzy search space;

[0048] S32. Determine the candidate values ​​for ambiguity and calculate the objective function value;

[0049] S33. If the fuzziness search space is empty, expand the search range and repeat step S32 until the fuzziness search space is not empty.

[0050] S34. The candidate fuzzy value for determining the minimum objective function value is the fixed fuzzy solution.

[0051] Furthermore, the specific steps for obtaining the fuzzy search space in step S31 are as follows:

[0052] Assuming that the two BeiDou antennas simultaneously track t+1 satellites at a single frequency, the double-difference observation equation can be written as:

[0053] P = -Gb(1.1);

[0054] Where, P∈R t×1 , G∈R t×3 b∈R 3×1 ;

[0055]

[0056] Where, Φ∈R t×1 , N∈Z t×1 ;

[0057] Where P and Φ are the double-difference pseudorange observation vector and the double-difference carrier phase observation vector, respectively, G is the double-difference observation matrix, b is the baseline vector, N is the integer ambiguity vector, and Z is the integer ambiguity vector. t×1 Let R represent an integer vector of size t × 1. t×1 Let R represent a real vector of size t × 1. t ×3 Let R represent a real vector of size t × 3. 3×1 Represents a 3×1 real number vector;

[0058] Given that the baseline length is known, equation (1.2) can be written as:

[0059]

[0060] Where b(θ,β)=[lcosθsinβ,lcosθcosβ,lsinθ] T θ and β are the pitch angle and yaw angle, respectively, and l is the baseline length;

[0061] Take the minimum value between the integer ambiguity vector and the baseline vector:

[0062]

[0063] Where N∈Zt×1 b∈R 3×1 , |b|=l;

[0064] in Q Φ Q P These are the covariance matrices of the double-difference carrier phase observations and the double-difference pseudorange observations, respectively.

[0065] Through orthogonal decomposition, we have:

[0066]

[0067] |b|=l(1.5);

[0068] in,

[0069] The objective function in equation (1.3) can be rewritten as:

[0070]

[0071] b(N) is the optimal baseline solution that minimizes F(N) under condition N;

[0072] The search is performed using equation (1.5), and a boundary value χ for the objective function is set. 2 Its search space is:

[0073]

[0074] The ambiguity within it must satisfy:

[0075]

[0076] Ignoring baseline length constraints and ambiguity, equation (1.9) represents a... Centered on, the shape is formed by Determined, volume is determined by χ 2 The three-dimensional coordinate ellipsoid space is determined;

[0077] Under the baseline length constraint, this space is the two-dimensional attitude domain search space, i.e.:

[0078]

[0079] According to equation (1.3), by using a sufficiently small search step, a traversal search is performed within this space to determine its corresponding fuzzy search space, i.e.:

[0080]

[0081] Furthermore, the method for quickly determining the search space based on orthogonal diagonal decomposition is as follows:

[0082] Decomposition by orthogonal diagonal It can be represented as:

[0083]

[0084] Where Λ is a diagonal matrix. for The eigenvalues ​​of S are denoted by S, where S is an orthogonal matrix, satisfying S T S = I. Let s = Sb(θ,β), Equation (1.9) can be rewritten as:

[0085]

[0086] Where s can be regarded as the new baseline vector after orthogonal transformation, and from |s|=l, s can be rewritten as:

[0087]

[0088] in and Let the pitch and heading angles represent the new baseline vector s. Substituting the above equation into equation (1.13) and rearranging, we get:

[0089]

[0090] in These are the three-dimensional coordinates of a vector;

[0091] Given the following three inequalities and a certain search step size:

[0092]

[0093]

[0094] Sure and Search scope and search points

[0095] Search through all attitude points Define the fuzzy search space;

[0096] At this time, Ω1(χ 2 Rewritten as:

[0097]

[0098] in,

[0099] The optimization strategy for the fuzzy search space is as follows:

[0100] The unconstrained linear least squares solution under condition N, without considering the baseline length constraint, is:

[0101]

[0102] set up The unconstrained linear least squares solution obtained by solving equation (1.20) under condition N without considering the baseline length constraint is as follows:

[0103] Since the sum of squared residuals of an unconstrained linear least squares solution is necessarily less than the sum of squared residuals of a constrained least squares solution, we can conclude that:

[0104]

[0105] Inequality in equation (1.21) As a basis for excluding pseudo-fuzziness candidate values;

[0106] After eliminating pseudo-fuzzyness candidate values ​​using the above inequalities, the objective function is then calculated.

[0107] Furthermore, the specific calculation method for the search step size is as follows:

[0108] With an ambiguity variation of 0.5 cycles as a constraint, the analytical search step size can be derived, resulting in the two-dimensional attitude search step size in the new coordinate system after unit orthogonal transformation. and

[0109] Assume G i S T =[k i1 ,k i2 ,k i2 ] T ,but:

[0110]

[0111]

[0112] Where i = 1, 2, ..., t.

[0113] Please refer to Figures 1 to 8 Embodiment 1 of the present invention is as follows:

[0114] Please refer to Figure 1A BeiDou orientation system includes a central processing module, two BeiDou baseband modules, and two BeiDou antennas mounted on a BeiDou orientation device. The two BeiDou baseband modules are connected to the two BeiDou antennas in a one-to-one correspondence. The central processing module includes an ARM service processing unit and a DSP algorithm processing unit. The ARM service processing unit and the DSP algorithm processing unit establish a communication connection. The ARM service processing unit is connected to the two BeiDou baseband modules respectively.

[0115] Please refer to Figure 1 It also includes a debug serial port unit, which is connected to the central processing module (the debug serial port unit is connected to both the ARM business processing unit and the DSP algorithm processing unit, but the DSP algorithm processing unit does not control the debug serial port unit).

[0116] Please refer to Figure 1 It also includes a TF card unit, which is connected to the central processing module (the TF card unit is connected to both the ARM business processing unit and the DSP algorithm processing unit, but the DSP algorithm processing unit does not control the TF card unit).

[0117] Please refer to Figure 1 It also includes a TL16C serial port expansion unit, which is connected to the central processing module (the TL16C serial port expansion unit is connected to both the ARM service processing unit and the DSP algorithm processing unit, but the DSP algorithm processing unit does not control the TL16C serial port expansion unit).

[0118] Please refer to Figure 1 It also includes a power supply unit, which is connected to the DSP algorithm processing unit.

[0119] The central processing module consists of a core board composed of a TI OMAPL138 chip, a 256MB memory chip, an eMMC storage chip, and related components. The TI OMAPL138 chip is an asymmetric multi-core processor combining DSP and ARM architectures, integrating the high digital signal processing performance of DSPs with the advantages of reduced instruction set computing (RISC) technology. The ARM core primarily handles integrated business logic, while the DSP core primarily handles data processing. The peripheral interfaces of the central processing module are connected to the serial ports of two BeiDou baseband modules via two sets of serial ports, UART0 and UART1, respectively, to receive data sent by the BeiDou baseband modules. A serial port, UART2, connects to a debugging serial port unit for human-machine interaction. An SDIO interface (SD0) connects to a TF card unit for TF card read / write functionality. An EMIF bus (EMIFA) connects to a TL16C serial port expansion unit for serial port expansion. The VCC_5V output from the power supply circuit unit connects to a set of VDD pins on the core board, providing a continuous and stable 5V power supply. The interface circuit diagram of the core board is shown below. Figure 2 As shown.

[0120] The BeiDou baseband module uses the Shanghai Sinan K706 dual-frequency high-precision positioning GNSS board. This board supports satellite signals such as BDS, GPS, and Galileo, and supports PVT and observation data output up to 50Hz. The serial port COM1 of the first BeiDou baseband module is connected to the serial port UART0 of the central processing module. The connection and disconnection of this communication line are controlled by DIP switch S1. The serial port COM1 of the second BeiDou baseband module is connected to the serial port UART1 of the central processing module. The connection and disconnection of this communication line are controlled by DIP switch S2. Both BeiDou baseband modules output ephemeris data and raw observation data to the central processing module at regular intervals of 1 second through their respective COM1 serial ports. The circuit connection diagram is shown below. Figure 3 As shown.

[0121] The BeiDou antenna used is a high-sensitivity GNSS antenna from Huace, supporting the reception of satellite signals such as BDS, GPS, and Galileo. Each of the two BeiDou baseband modules is connected to one BeiDou antenna. The straight-line distance between the two BeiDou antennas is the baseline length, which can be measured using measuring tools such as a tape measure. Generally, the measurement result can be accurate to the millimeter level (this baseline length data is required in the DSP software). Considering the working mechanism and characteristics of the BeiDou orientation equipment, these two BeiDou antennas should be placed in an open area with no obstructions and must be higher than the surrounding ground level. Figure 4 The image shows an example of the structural installation of a BeiDou antenna in a BeiDou orientation device.

[0122] The debug serial port unit consists of a MAX3232EU chip and other related circuits. One TTL signal interface of the MAX3232 chip is connected to the UART2 of the central processing module, and its corresponding RS232 signal interface is connected to socket X5, ultimately connecting to the serial port on the PC. Another TTL signal interface of the MAX3232 chip is connected to the TXB / RXB interface of the serial port expansion unit, and its corresponding RS232 signal interface is connected to socket X6 as a backup interface. To improve the anti-static capability of the debug serial port unit, an ESD device (electrostatic discharge protection diode) is designed on the RS232 signal line connecting to the PC socket to protect the components of the debug serial port unit. Through the debug serial port unit, development and maintenance personnel can transmit software programming and upgrade commands and set device operating parameters. Part of the circuitry of the debug serial port unit is shown below. Figure 5 As shown.

[0123] The TF card unit consists of a TF card slot and related circuitry. This TF card unit connects to the SDIO interface of the core board. Each signal in the SDIO interface of the TF card unit circuit is connected to a 10KΩ pull-up resistor to improve signal stability and circuit reliability. The TF card's power supply voltage VDD is 3.3V. This voltage circuit connects a capacitor of several hundred picofarads to ground to ensure the stability of the TF card voltage and prevent power supply voltage fluctuations from affecting the circuitry. Through the TF card unit, development and maintenance personnel can quickly burn and upgrade system software. This function is used in conjunction with the debugging serial port unit. Part of the circuitry of the TF card unit is shown below. Figure 6 As shown.

[0124] The TL16C serial port expansion unit consists of a TL16C752DPFBR chip and related peripheral circuits. This expansion unit is connected to the EMIF bus of the core board. A 22.1184MHz crystal oscillator is used. This expansion unit provides two serial ports (one for communication with an external host, and the other as a backup). Both sets of serial port signals are TTL signals. The TXA and RXA lines are connected to an ESD device (electrostatic discharge protection tube) with the reference designation V8 to prevent damage to electronic components from electrostatic discharge introduced through socket X4. The RXA and RXB pins of the TLC16C752DPFBR chip are each connected to a 10KΩ pull-up resistor to improve the stability of the received serial port signal. Part of the circuitry of the TL16C serial port expansion unit is shown below. Figure 7 As shown.

[0125] The power supply unit consists of two TPS5420D chips and related circuitry. The input voltage of this power supply unit is 9V–25V, and it outputs two power supplies (one 5V and the other 3.3V). The 5V power supply powers the central processing module and the Beidou baseband module; the 3.3V power supply powers the debugging serial port unit, the TF card unit, and the TL16C serial port expansion unit. The output voltage of the TPS5420D chip in this power supply unit is mainly determined by the ratio of the two voltage divider resistors connected to the VSNS pin of the chip. The VSNS pin is a feedback reference level pin, and its voltage is constant at 1.221V. The output power supply VCC_5V is divided by resistors R02 and R0; the output power supply VCC_3V3 is divided by resistors R05 and R07. The voltage is calculated using the formula VCC_5V = V... VSNS / (V R04 / (V R04 +V R02 The output power supply voltage VCC_5V can be calculated using the formula VCC_3V3 = V VSNS / (V R07 / (V R07 +V R05 The output voltage VCC_3V3 can be calculated; part of the power supply unit circuit is as follows: Figure 8 As shown.

[0126] This BeiDou orientation system design utilizes an ARM core + DSP core architecture. These two cores process data relatively independently, achieving true synchronous and concurrent processing of data transmission and reception as well as data algorithms. Both the ARM and DSP cores run real-time systems, ensuring real-time data processing. Furthermore, the two cores interact via shared memory, enabling efficient data processing. The ARM core of the central processing module handles comprehensive business data, while the DSP core leverages its powerful digital signal processing capabilities to handle algorithmic tasks. This combination fully utilizes the unique advantages of each core, maximizing the optimal performance of the central processing module. In this scheme, the auxiliary antenna, relative to the main antenna, operates within the same area based on satellite observation data. The dual-difference observation equation formed by the two antennas eliminates or reduces various errors caused by signal propagation (e.g., atmospheric errors, satellite clock errors), thereby achieving high-precision differential orientation and effectively improving orientation accuracy. This scheme utilizes baseline lengths accurate to millimeters and other verification information to calculate azimuth data with higher accuracy and better stability. Under static conditions, the longer the operating time, the higher the orientation accuracy.

[0127] Please refer to Figure 9 Embodiment two of the present invention is as follows:

[0128] A BeiDou orientation method, applied to the BeiDou orientation system of Embodiment 1, the BeiDou orientation method includes the following steps:

[0129] S1. The Beidou baseband module sends ephemeris data and raw observation data to the ARM service processing unit;

[0130] S2. The ARM service processing unit receives the ephemeris data and raw observation data, and sends them to the DSP algorithm processing unit;

[0131] S3. The DSP algorithm processing unit receives the ephemeris data and the raw observation data, and performs calculations and processing based on the ephemeris data and the raw observation data to obtain the position data and direction data of the Beidou orientation device.

[0132] S4. The DSP algorithm processing unit sends the position data and direction data to the ARM service processing unit;

[0133] S5. The ARM service processing unit outputs the azimuth data, device status data, and version data of the Beidou orientation device based on the location data and direction data.

[0134] In step S3, the DSP algorithm processing unit performs a fuzzy search algorithm for the value range, and the fuzzy search algorithm includes the following steps:

[0135] S31. Initialize the search step size and fuzzy search space;

[0136] S32. Determine the candidate values ​​for ambiguity and calculate the objective function value;

[0137] S33. If the fuzziness search space is empty, expand the search range and repeat step S32 until the fuzziness search space is not empty.

[0138] S34. The candidate fuzzy value for determining the minimum objective function value is the fixed fuzzy solution.

[0139] The specific steps for obtaining the fuzzy search space in step S31 are as follows:

[0140] Establishment of the pose domain-integer least squares search model:

[0141] Assuming that the two BeiDou antennas simultaneously track t+1 satellites at a single frequency, the double-difference observation equation can be written as:

[0142] P = -Gb (1.1);

[0143] Where, P∈R t×1 , G∈R t×3 b∈R 3×1 ;

[0144]

[0145] Where, Φ∈R t×1 , N∈Z t×1 ;

[0146] Where P and Φ are the double-difference pseudorange observation vector and the double-difference carrier phase observation vector, respectively, G is the double-difference observation matrix, b is the baseline vector, N is the integer ambiguity vector, and Z is the integer ambiguity vector. t×1 Let R represent an integer vector of size t × 1. t×1 Let R represent a real vector of size t × 1. t ×3 Let R represent a real vector of size t × 3. 3×1 Represents a 3×1 real number vector;

[0147] Given that the baseline length is known, equation (1.2) can be written as:

[0148]

[0149] Where b(θ,β)=[lcosθsinβ,lcosθcosβ,lsinθ] T θ and β are the pitch angle and yaw angle, respectively, and l is the baseline length;

[0150] The integer ambiguity in the above formula can be regarded as a function of attitude. By traversing and searching in the two-dimensional attitude domain with a sufficiently small step size, all possible ambiguity candidate values ​​can be obtained.

[0151] When the baseline length is known, and the ambiguity is fixed using the least squares principle, all observation information needs to be weighted within the objective function. The process of solving for the ambiguity and baseline vector, in order to solve the minimization problem, is as follows:

[0152] Take the minimum value between the integer ambiguity vector and the baseline vector:

[0153]

[0154] Where N∈Z t×1 b∈R 3×1 , |b|=l;

[0155] in Q Φ Q P These are the covariance matrices of the double-difference carrier phase observations and the double-difference pseudorange observations, respectively.

[0156] Through orthogonal decomposition, we have:

[0157]

[0158] |b|=l(1.5);

[0159] in,

[0160] The minimization problem in equation (1.3) is equivalent to minimizing the sum of the second and third terms in equation (1.4). Therefore, the objective function in equation (1.3) can be rewritten as:

[0161]

[0162] b(N) is the optimal baseline solution that minimizes F(N) under condition N;

[0163] The first term in equation (1.5) can be considered as a term related to ambiguity, and the second term can be considered as a term related to baseline. A search is performed using equation (1.5), and a boundary value χ for the objective function is set. 2 Its search space is:

[0164]

[0165] The ambiguity within it must satisfy:

[0166]

[0167] Ignoring baseline length constraints and ambiguity, equation (1.9) represents a... Centered on, the shape is formed by Determined, volume is determined by χ 2 The three-dimensional coordinate ellipsoid space is determined;

[0168] Under the baseline length constraint, this space is the two-dimensional attitude domain search space, i.e.:

[0169]

[0170] According to equation (1.3), by using a sufficiently small search step, a traversal search is performed within this space to determine its corresponding fuzzy search space, i.e.:

[0171]

[0172] The fast method for determining the search space based on orthogonal diagonal decomposition is as follows:

[0173] Theoretically, we can determine the attitude domain search range using equation (1.9), but It's not a diagonal matrix, which affects search efficiency; It is the variance and covariance matrix of the baseline vector floating-point solution, and therefore must satisfy the real symmetry and positive definite conditions.

[0174] Decomposition via orthogonal diagonal It can be represented as:

[0175]

[0176] Where Λ is a diagonal matrix. for The eigenvalues ​​of S are denoted by S, where S is an orthogonal matrix, satisfying S T S = I. Let s = Sb(θ,β), Equation (1.9) can be rewritten as:

[0177]

[0178] Here, s can be regarded as the new baseline vector after orthogonal transformation. From |s|=l, s can be rewritten as:

[0179]

[0180] in and Let the pitch and heading angles represent the new baseline vector s. Substituting the above equation into equation (1.13) and rearranging, we get:

[0181]

[0182] in, These are the three-dimensional coordinates of a vector;

[0183] Given the following three inequalities and a certain search step size:

[0184]

[0185]

[0186] Sure and Search scope and search points

[0187] Search through all attitude points Define the fuzzy search space;

[0188]

[0189] in,

[0190] The optimization strategy for the fuzzy search space is as follows:

[0191] Theoretically, determining all ambiguity spaces Ω1(χ) 2After that, the objective function value F(N) can be calculated using the ambiguity candidate values, thus fixing the ambiguity. However, calculating the objective function value F(N) requires solving the optimal conditional baseline solution b(N) in equation (1.7). Under the baseline length constraint, solving b(N) is a constrained least squares problem without an analytical expression. The solution process involves iteration and is quite complex. Too many ambiguity candidate values ​​mean that equation (1.7) needs to be solved multiple times, which will seriously affect the computational efficiency.

[0192] In fact, when using equation (1.9) to determine the attitude domain search space, the ambiguity-related term in F(N) is not considered, which inevitably leads to Ω1(χ 2 There are a large number of pseudo-fuzziness candidate values, and these pseudo-candidate values ​​are not in Ω(χ). 2 In order to improve the efficiency of the solution, it is necessary to eliminate pseudo-fuzziness candidate values ​​as much as possible.

[0193] The unconstrained linear least squares solution under condition N, without considering the baseline length constraint, is:

[0194]

[0195] set up The unconstrained linear least squares solution obtained by solving equation (1.20) under condition N without considering the baseline length constraint is as follows:

[0196] Since the sum of squared residuals of an unconstrained linear least squares solution is necessarily less than the sum of squared residuals of a constrained least squares solution, we can conclude that:

[0197]

[0198] Inequality in equation (1.21) As a basis for excluding pseudo-fuzziness candidate values;

[0199] After eliminating pseudo-fuzzyness candidate values ​​using the above inequalities, the objective function is then calculated.

[0200] The specific method for calculating the search step size is as follows:

[0201] With an ambiguity variation of 0.5 cycles as a constraint, the analytical search step size can be derived, resulting in the two-dimensional attitude search step size in the new coordinate system after unit orthogonal transformation. and

[0202] Assume G i S T =[k i1 ,k i2 ,k i2 ] T ,but:

[0203]

[0204]

[0205] Where i = 1, 2, ..., t.

[0206] The accuracy of the final solution obtained by this design scheme is comparable to that of the standard iterative algorithm, but the computational efficiency is much higher than that of the standard iterative algorithm, which meets the requirement of the directional device to achieve rapid orientation through dual antennas; the two cores of the central processing module work independently and cooperate with each other, giving full play to the advantages of each core of the central processing module.

[0207] In terms of software design, the integer least squares principle and attitude domain search method are combined to establish an attitude domain-integer least squares search model. This model fully considers all observation information and prior information during the ambiguity search and fixation process, has an analytical attitude domain search space, and has a high success rate and reliability. It can meet the fast and reliable requirements of GNSS (Global Navigation Satellite System) orientation.

[0208] The BeiDou orientation system and method designed in this scheme can be applied to fields with high-precision and rapid positioning and orientation requirements, such as portable TACAN ground stations, aircraft attitude measurement, initial alignment of inertial navigation systems, auxiliary missile launch azimuth determination, and deformation monitoring. In the field of high-precision and rapid orientation, this scheme has high orientation accuracy and low cost.

[0209] In summary, the BeiDou orientation system and method provided by this invention comprises a central processing module, two BeiDou baseband modules, and two BeiDou antennas, all mounted on a BeiDou orientation device. The two BeiDou baseband modules are connected one-to-one with the two BeiDou antennas. The central processing module includes an ARM service processing unit and a DSP algorithm processing unit. The ARM service processing unit is connected to each of the two BeiDou baseband modules and receives data transmitted from them. A communication connection is established between the ARM service processing unit and the DSP algorithm processing unit. The ARM service processing unit transmits data to the DSP algorithm processing unit via shared memory, and the DSP algorithm processing unit quickly processes the transmitted data. After solving and processing the direction data, the direction data is sent back to the ARM business processing unit. By using an ARM core + DSP core mode, the two cores process data relatively independently, which can truly realize the synchronous and concurrent processing of data transmission and reception and data algorithms. The ARM business processing unit and the DSP algorithm processing unit interact with each other through shared memory, which can achieve efficient data processing. The ARM core processes the data of comprehensive business, while the DSP algorithm processing unit uses its powerful digital signal processing capabilities to handle the algorithm work. This combination fully utilizes the unique advantages of the two cores, maximizes the optimal efficiency of the central processing module, and thus effectively improves the BeiDou orientation accuracy.

[0210] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent modifications made based on the content of the present invention specification and drawings, or direct or indirect applications in related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A BeiDou orientation method, characterized in that, Includes the following steps: S1. The Beidou baseband module sends ephemeris data and raw observation data to the ARM service processing unit. S2, the ARM service processing unit receives the ephemeris data and raw observation data, and sends them to the DSP algorithm processing unit; S3, the DSP algorithm processing unit receives the ephemeris data and the raw observation data, and performs calculations and processing based on the ephemeris data and the raw observation data to obtain the position data and direction data of the Beidou orientation device; S4. The DSP algorithm processing unit sends the position data and direction data to the ARM service processing unit. S5. The ARM business processing unit outputs the azimuth data, device status data, and version data of the Beidou orientation device based on the location data and direction data. In step S3, the DSP algorithm processing unit performs a fuzzy search algorithm for the value range, and the fuzzy search algorithm includes the following steps: S31. Initialize the search step size and obtain the fuzzy search space; S32. Determine the candidate values ​​for ambiguity and calculate the objective function value; S33. If the fuzziness search space is empty, expand the search range and repeat step S32 until the fuzziness search space is not empty. S34. The candidate ambiguity value for determining the minimum objective function value is the fixed ambiguity solution; The specific steps for obtaining the fuzzy search space in step S31 are as follows: Assuming two BeiDou antennas simultaneously track t+1 satellites at a single frequency, the double-difference observation equation can be written as: P = -Gb(1.1); Where, P∈R t×1 , G∈R t×3 b∈R 3×1 ; Where, Φ∈R t×1 , N∈Z t×1 ; Where P and Φ are the double-difference pseudorange observation vector and the double-difference carrier phase observation vector, respectively, G is the double-difference observation matrix, b is the baseline vector, N is the integer ambiguity vector, and Z is the integer ambiguity vector. t×1 Let R represent an integer vector of size t × 1. t×1 Let R represent a real vector of type t × 1. t×3 Let R represent a real vector of size t × 3. 3×1 Represents a 3×1 real vector; Given that the baseline length is known, equation (1.2) can be written as: Where b(θ,β)=[lcosθsinβ,lcosθcosβ,lsinθ] T θ and β are the pitch angle and yaw angle, respectively, and l is the baseline length; Take the minimum value between the integer ambiguity vector and the baseline vector: Where N∈Z t×1 b∈R 3×1 , |b|=l; in Q Φ Q P These are the covariance matrices of the double-difference carrier phase observations and the double-difference pseudorange observations, respectively. Through orthogonal decomposition, we have: |b|＝l (1.5)； in, The objective function in equation (1.3) can be rewritten as: in, b(N) is the optimal baseline solution that minimizes F(N) under condition N; The search is performed using equation (1.5), and a boundary value χ for the objective function is set. 2 Its search space is: The ambiguity within it must satisfy: Ignoring baseline length constraints and ambiguity, equation (1.9) represents a... Centered on, the shape is formed by Determined, volume is determined by χ 2 The three-dimensional coordinate ellipsoid space is determined; Under the baseline length constraint, this space is the two-dimensional attitude domain search space, i.e.: According to equation (1.3), by using a sufficiently small search step, a traversal search is performed within this space to determine its corresponding fuzzy search space, i.e.:

2. The BeiDou orientation method according to claim 1, characterized in that, The fast method for determining the search space based on orthogonal diagonal decomposition is as follows: Decomposition via orthogonal diagonal Represented as: Where Λ is a diagonal matrix. for The eigenvalues ​​of S are denoted by S, where S is an orthogonal matrix, satisfying S T S = I, let s = Sb(θ,β) Equation (1.9) can be rewritten as: Where s is the new baseline vector after orthogonal transformation, and from |s|=l, s can be rewritten as: in and Let the pitch and heading angles represent the new baseline vector s. Substituting the above equation into equation (1.13) and rearranging, we get: in These are the three-dimensional coordinates of a vector; Given the following three inequalities and a certain search step size: Sure and Search range and attitude search points Search through all attitude points Define the fuzzy search space; At this time, Ω1(χ 2 Rewritten as: in, 3. The BeiDou orientation method according to claim 2, characterized in that, The optimization strategy for the fuzzy search space is as follows: The unconstrained linear least squares solution under condition N, without considering the baseline length constraint, is: set up The unconstrained linear least squares solution obtained by solving equation (1.20) under condition N without considering the baseline length constraint is as follows: Since the sum of squared residuals of an unconstrained linear least squares solution is necessarily less than the sum of squared residuals of a constrained least squares solution, we can conclude that: Inequality in equation (1.21) As a basis for excluding pseudo-fuzziness candidate values; After eliminating pseudo-fuzzyness candidate values ​​using the above inequalities, the objective function is then calculated.

4. The BeiDou orientation method according to claim 1, characterized in that, The specific method for calculating the search step size is as follows: With an ambiguity variation of 0.5 cycles as a constraint, the analytical search step size can be derived, resulting in the two-dimensional attitude search step size in the new coordinate system after unit orthogonal transformation. and Assume G i S T =[k i1 ,k i2 ,k i3 ] T ,but: Where i = 1, 2, ..., t.

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