A parameter optimization method for satellite-inertial navigation depth combination receiver based on error model

Abstract

This invention discloses a method for optimizing parameters for a deep-integrated satellite-inertial navigation receiver based on an error model. The method involves modeling the phase error of the deep-integrated navigation receiver, measuring the receiver's acceleration and signal-to-noise ratio, and assisting the receiver in selecting optimal loop bandwidth parameters. The method measures receiver acceleration using an inertial device and the signal-to-noise ratio using the receiving loop. Based on the deep-integrated navigation phase error model, the receiver is assisted in determining the optimal loop parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of satellite / inertial combined navigation systems, and in particular to a method for optimizing parameters of a satellite / inertial navigation combined receiver based on an error model. Background Art

[0002] Satellite navigation provides high-precision navigation around the clock for users worldwide. However, in obstructed environments like cities and tunnels, satellite navigation signal quality can degrade or become unavailable. Inertial navigation, an autonomous navigation method unaffected by the external electromagnetic environment, can only maintain high-precision navigation for a short period of time, with errors growing over time. Therefore, satellite and inertial navigation complement each other, and a dual-system combination can significantly improve receiver navigation performance.

[0003] Deep combining is a form of integrated navigation. By directly incorporating inertial navigation system measurements into the satellite navigation signal reception loop filter, deep combining can compensate for the dynamic errors of the satellite navigation loop, improve reception sensitivity, and maximize the advantages of dual-system integrated navigation. For a deep-integrated navigation receiver with a fixed hardware configuration, loop bandwidth is the most critical factor affecting system performance. Excessive bandwidth will reduce the reception sensitivity of satellite navigation signals, while too small bandwidth will result in poor dynamic adaptability of the receiver. Existing methods typically design the receiver loop bandwidth to a fixed value based on experience in different operating environments, or adjust the loop bandwidth based on the carrier-to-noise ratio of the received signal. However, these methods fail to consider the impact of receiver dynamics and the deep combining structure on system error performance, and are not optimal loop parameter configurations.

[0004] Therefore, the existing technology has defects and needs to be improved and developed. Summary of the Invention

[0005] To solve the above problems, the present invention proposes a parameter optimization method for a deep-integrated satellite-inertial navigation receiver based on an error model. The method aims to establish a deep-integrated navigation phase error model, measure the receiver acceleration through inertial devices, and measure the signal-to-noise ratio through the receiving loop. Based on the deep-integrated navigation phase error model, the receiver is assisted in making decisions on the optimal loop parameters.

[0006] To achieve the above object, the present invention provides a method for optimizing parameters of a satellite-inertial navigation combined receiver based on an error model, comprising the following steps:

[0007] Establish a phase error model for deep integrated navigation receivers;

[0008] Measure receiver acceleration and satellite navigation signal carrier-to-noise ratio;

[0009] Obtain the error coefficient of the inertial device;

[0010] The receiver acceleration, the satellite navigation signal carrier-to-noise ratio and the inertial device error coefficient are input into the deep integrated navigation receiver phase error model, the relationship between the total phase error and the loop bandwidth of the deep integrated navigation receiver is calculated, and the optimal loop bandwidth parameter of the deep integrated navigation receiver is obtained.

[0011] Preferably, the deep integrated navigation receiver phase error model is:

[0012]

[0013] Where s represents the Laplace domain, θ i (s) is the input signal phase, θ o (s) is the output signal phase, K a is the accelerometer scale factor error, θ clk (s) is the crystal oscillator error, w(s) is the noise error, Δf IMU (s) is the linear error;

[0014] The system function of the second-order loop is recorded as:

[0015]

[0016] Among them, K d , K0 are the phase detector gain and voltage controlled oscillator gain respectively, ω n is the characteristic frequency, ξ is the damping coefficient,

[0017] Preferably, the receiver acceleration is measured by:

[0018] The receiver acceleration is obtained from an output result of an inertial navigation system.

[0019] Preferably, the method for measuring the carrier-to-noise ratio of the satellite navigation signal is:

[0020] The carrier-to-noise ratio of the satellite navigation signal is estimated using the mean-variance ratio to obtain:

[0021]

[0022]

[0023] Among them, MVR is the mean variance ratio, I i is the integration result of the in-phase branch of N coherent integration periods in satellite navigation signal processing, i = 1, 2, …, N; E(*) represents the mathematical expectation; Var(*) represents the variance; T is the total time length of N coherent integration periods; C / N0 is the signal-to-noise ratio estimate.

[0024] Preferably, the inertial device error coefficient is:

[0025] The error coefficients of typical inertial devices are as follows: the initial bias values ​​of the accelerometer and gyroscope are 100 mGal and 5 deg / h respectively; the initial velocity error and initial attitude error are 1×10 -2 m / s and 5×10 -2 deg; the measurement bandwidth of the accelerometer and gyroscope is 100 Hz; the power spectral density of the white noise of the accelerometer and gyroscope are and The power spectral density of the Gauss-Markov driven noise of the accelerometer and gyroscope is 1×10 -8 (m / s 3 ) 2 / Hz and 1×10 -8 (deg / s 2 ) 2 / Hz; the error correlation time of the accelerometer and gyroscope is 1.7 hours.

[0026] Preferably, the loop bandwidth of the deep integrated navigation receiver is:

[0027]

[0028] Where f represents the frequency domain after Fourier transform.

[0029] Preferably, the total phase error is:

[0030]

[0031] Among them, δθ w ,δθ clk ,δθ Ka 、 are the error terms introduced by noise, crystal oscillator, inertial device proportional factor and inertial device linear factor after filtering.

[0032] Preferably, the method for obtaining the optimal loop bandwidth parameter of the deep integrated navigation receiver is:

[0033] Receiver acceleration is measured by an inertial navigation system;

[0034] Measuring the carrier-to-noise ratio of satellite navigation signals through a satellite navigation receiver loop;

[0035] Obtain the inertial device error coefficient through the factory test parameters of the inertial device;

[0036] The receiver acceleration, the satellite navigation signal carrier-to-noise ratio and the inertial device error coefficient are input into the deep integrated navigation receiver phase error model to calculate the total phase error δθ totThe loop bandwidth B of the deep integrated navigation receiver L The relationship to the total phase error δθ tot The minimum is the optimization target, which assists the deep integrated navigation receiver to select the optimal loop bandwidth parameters.

[0037] Compared with the prior art, the present invention has the following advantages and technical effects:

[0038] The present invention provides a parameter optimization method for a deep-integrated satellite-inertial navigation receiver based on an error model. The specific implementation steps include: modeling the phase error of the deep-integrated navigation receiver, measuring the receiver acceleration and signal-to-noise ratio, and assisting the receiver in selecting the optimal loop bandwidth parameters. By measuring the receiver acceleration and signal-to-noise ratio, inputting the inertial device error coefficients, and minimizing the deep-integrated navigation receiver phase error as the criterion, the receiver is assisted in selecting the optimal loop bandwidth parameters. This method addresses the problem in traditional methods of selecting receiver bandwidth parameters that fail to consider the influence of receiver dynamics and deep-integrated structure, further improving the error performance of the deep-integrated system. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of this application. The exemplary embodiments and descriptions of this application are intended to explain this application and do not constitute an improper limitation on this application. In the accompanying drawings:

[0040] Figure 1 This is a flowchart of a specific implementation of a method for optimizing parameters of a satellite-inertial navigation deep combination receiver based on an error model according to the present invention.

[0041] Figure 2 It is a structural schematic diagram of a deep integrated navigation receiver described in a method for optimizing parameters of a satellite inertial navigation deep integrated receiver based on an error model of the present invention.

[0042] Figure 3 The invention discloses a deep combination phase error Laplace domain system transmission block diagram of a satellite inertial navigation deep combination receiver parameter optimization method based on an error model.

[0043] Figure 4 This is a preferred embodiment of the present invention using a method for optimizing parameters of a satellite-inertial navigation deep combination receiver based on an error model. DETAILED DESCRIPTION

[0044] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0045] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0046] See Figure 1 , Figure 1 This is a flowchart of a method for optimizing parameters of a satellite-inertial navigation combined receiver based on an error model. Figure 1 As shown, the present invention implements the following steps when performing optimal parameter auxiliary decision-making:

[0047] 1. Establish a deep integrated navigation receiver phase error model

[0048] See Figure 2 , Figure 2 This is a schematic diagram of the structure of a deep integrated navigation receiver according to a method for optimizing parameters of a deep integrated satellite inertial navigation receiver based on an error model of the present invention. Figure 2 The Laplace domain system transmission block diagram that can abstract the deep combined phase error is shown in Figure 3 .

[0049] according to Figure 3 , it can be concluded that the phase error model of the deep integrated navigation receiver is specifically:

[0050]

[0051] Where s represents the Laplace domain, θ i (s) is the input signal phase, θ o (s) is the output signal phase, K a is the accelerometer scale factor error, θ clk (s) is the crystal oscillator error, w(s) is the noise error, Δf IMU (s) is the linear error.

[0052] For the navigation receiver, the system function of the second-order loop can be expressed as:

[0053]

[0054] Among them, K d , K0 are the phase detector gain and voltage controlled oscillator gain respectively, ω n is the characteristic frequency, ξ is the damping coefficient,

[0055]

[0056] The loop bandwidth of a deep integrated navigation receiver is defined as:

[0057]

[0058] Where f represents the frequency domain after Fourier transform.

[0059] According to the definition of the phase error of the navigation receiver tracking loop, the total phase error δθ can be written as tot The expression is:

[0060]

[0061] Among them, δθ w ,δθ clk ,δθ Ka 、 are the error terms introduced by noise, crystal oscillator, inertial device proportional factor and inertial device linear factor after filtering. tot It is related to the signal-to-noise ratio, inertial device accuracy, receiver acceleration and loop bandwidth.

[0062] 2. Measure receiver acceleration and satellite navigation signal carrier-to-noise ratio

[0063] The receiver acceleration is directly obtained from the output of the inertial navigation system. The mean variance ratio (MVR) method is used to estimate the carrier-to-noise ratio of the satellite navigation signal:

[0064]

[0065]

[0066] Among them, I i is the integration result of the in-phase branch of N coherent integration periods in satellite navigation signal processing, i = 1, 2, …, N; E(*) represents the mathematical expectation; Var(*) represents the variance; T is the total time length of N coherent integration periods; C / N0 is the signal-to-noise ratio estimate.

[0067] 3. Obtain the error coefficient of the inertial device

[0068] For example analysis, the error coefficients of typical inertial devices are as follows: the initial bias values ​​of the accelerometer and gyroscope are 100 mGal and 5 deg / h respectively; the initial velocity error and initial attitude error are 1×10 -2 m / s and 5×10 -2 deg; the measurement bandwidth of the accelerometer and gyroscope is 100 Hz; the power spectral density of the white noise of the accelerometer and gyroscope are and The power spectral density of the Gauss-Markov driven noise of the accelerometer and gyroscope is 1×10 -8 (m / s 3 ) 2 / Hz and 1×10 -8 (deg / s 2 ) 2 / Hz; the error correlation time of the accelerometer and gyroscope is 1.7 hours.

[0069] In actual application, the error coefficient of the inertial device is obtained through the factory test parameters of the inertial device.

[0070] 4. Determine the optimal bandwidth based on the deep integrated navigation receiver phase error model

[0071] The receiver acceleration measured by the inertial navigation system, the satellite navigation signal carrier-to-noise ratio measured by the satellite navigation receiver loop, and the inertial device error coefficient obtained by the inertial device factory test parameters are input into the deep integrated navigation receiver phase error model to calculate the total phase error δθ tot The loop bandwidth B of the deep integrated navigation receiver L The relationship between δθ tot The minimum is the optimization target, which assists the deep integrated navigation receiver to select the optimal loop bandwidth parameters.

[0072] See Figure 4 , Figure 4 This is the result of calculating the optimal bandwidth of a deep integrated navigation receiver under different receiver accelerations (with gravitational acceleration g as a reference) and different satellite navigation signal carrier-to-noise ratios using the typical parameters of step 3 according to the error model-based parameter optimization method of the present invention. It can be seen that the greater the receiver acceleration, the larger the optimal bandwidth; the lower the signal-to-noise ratio, the smaller the optimal bandwidth. This is because when the acceleration is large, the dynamic information auxiliary error provided by the inertial navigation system is larger, and the deep integrated system needs to increase the loop bandwidth to process the dynamic error; when the signal-to-noise ratio is low, the deep integrated system needs to reduce the loop bandwidth and increase the signal processing gain.

[0073] It can be seen that the error model-based parameter optimization method for deep-integrated satellite-inertial navigation receivers proposed in the present invention can measure the receiver acceleration through inertial devices and the signal-to-noise ratio through the receiving loop, and assist the receiver in making decisions on the optimal loop parameters based on the deep-integrated navigation phase error model.

[0074] In summary, the present invention provides an error model-based parameter optimization method for deep-integrated satellite-inertial navigation receivers: deep-integrated navigation receiver error modeling, receiver acceleration and signal-to-noise ratio measurements, and assistance in selecting optimal loop bandwidth parameters for the receiver. By measuring receiver acceleration using inertial devices and the signal-to-noise ratio using the receiving loop, the receiver is assisted in determining optimal loop parameters based on the deep-integrated navigation phase error model. This method addresses the problem in traditional methods of selecting receiver bandwidth parameters that fail to consider the effects of receiver dynamics and deep-integrated architecture, further improving the error performance of deep-integrated systems.

[0075] The above are merely preferred embodiments of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for optimizing parameters of a satellite-inertial navigation receiver based on an error model, characterized in that: The following steps are involved: Establish a phase error model for deep integrated navigation receivers; Measure receiver acceleration and satellite navigation signal carrier-to-noise ratio; Obtain the error coefficient of the inertial device; The receiver acceleration, the satellite navigation signal carrier-to-noise ratio and the inertial device error coefficient are input into the deep integrated navigation receiver phase error model, the relationship between the total phase error and the loop bandwidth of the deep integrated navigation receiver is calculated, and the optimal loop bandwidth parameter of the deep integrated navigation receiver is obtained.

2. The parameter optimization method for satellite-inertial navigation deep combination receiver based on error model according to claim 1 is characterized in that: The phase error model of the deep integrated navigation receiver is: Where s represents the Laplace domain, θ i (s) is the input signal phase, θ o (s) is the output signal phase, K a is the accelerometer scale factor error, θ clk (s) is the crystal oscillator error, w(s) is the noise error, Δf IMU (s) is the linear error; The system function of the second-order loop is recorded as: Among them, K d , K0 are the phase detector gain and voltage controlled oscillator gain respectively, ω n is the characteristic frequency, ξ is the damping coefficient, 3. The parameter optimization method for satellite-inertial navigation deep combination receiver based on error model according to claim 1, characterized in that: The receiver acceleration is measured as follows: The receiver acceleration is obtained from an output result of an inertial navigation system.

4. The method for optimizing parameters of a satellite-inertial navigation receiver based on an error model according to claim 1, wherein: The method for measuring the carrier-to-noise ratio of the satellite navigation signal is: The carrier-to-noise ratio of the satellite navigation signal is estimated using the mean-variance ratio to obtain: Among them, MVR is the mean variance ratio, I i is the integration result of the in-phase branch of N coherent integration periods in satellite navigation signal processing, i = 1, 2, …, N; E(*) represents the mathematical expectation; Var(*) represents the variance; T is the total time length of N coherent integration periods; C / N0 is the signal-to-noise ratio estimate.

5. The parameter optimization method for satellite-inertial navigation deep combination receiver based on error model according to claim 1, characterized in that: The inertial device error coefficient is: The error coefficients of typical inertial devices are as follows: the initial bias values ​​of the accelerometer and gyroscope are 100 mGal and 5 deg / h respectively; the initial velocity error and initial attitude error are 1×10 -2 m / s and 5×10 -2 deg; The measurement bandwidth of the accelerometer and gyroscope is 100 Hz; the power spectral density of the white noise of the accelerometer and gyroscope are and The power spectral density of the Gauss-Markov driven noise of the accelerometer and gyroscope is 1×10 -8 (m / s 3 ) 2 / Hz and 1×10 -8 (deg / s 2 ) 2 / Hz; the error correlation time of the accelerometer and gyroscope is 1.7 hours.

6. The method for optimizing parameters of a satellite-inertial navigation receiver based on an error model according to claim 5, wherein: The loop bandwidth of the deep integrated navigation receiver is: Where f represents the frequency domain after Fourier transform.

7. The method for optimizing parameters of a satellite-inertial navigation receiver based on an error model according to claim 6, wherein: The total phase error is: Among them, δθ w ,δθ clk ,δθ Ka 、 are the error terms introduced by noise, crystal oscillator, inertial device proportional factor and inertial device linear factor after filtering.

8. The method for optimizing parameters of a satellite-inertial navigation receiver based on an error model according to claim 7, wherein: The method for obtaining the optimal loop bandwidth parameter of the deep integrated navigation receiver is: Receiver acceleration is measured by an inertial navigation system; Measuring the carrier-to-noise ratio of satellite navigation signals through a satellite navigation receiver loop; Obtain the inertial device error coefficient through the factory test parameters of the inertial device; The receiver acceleration, the satellite navigation signal carrier-to-noise ratio and the inertial device error coefficient are input into the deep integrated navigation receiver phase error model to calculate the total phase error δθ tot The loop bandwidth B of the deep integrated navigation receiver L The relationship to the total phase error δθ tot The minimum is the optimization target, which assists the deep integrated navigation receiver to select the optimal loop bandwidth parameters.

Images