An ionospheric anomaly simulation method for satellite landing system receiver testing

Abstract

A method for simulating ionospheric anomaly for testing a satellite landing system receiver includes: setting motion parameters for an ionospheric anomaly scenario; setting relevant parameters for an ionospheric threat model, wherein the ionospheric threat model includes a wedge model for simulating ionospheric delay anomaly under an ionospheric storm and a trapezoidal model for simulating ionospheric delay anomaly under a plasma bubble; setting parameters for an ionospheric anomaly space model based on relative motion, wherein the ionospheric anomaly space model describes the relative motion between an ionospheric scintillation model and an ionospheric threat model; setting parameters for a phase screen model, wherein the phase screen model parameters are parameters of a double-power-law phase screen model; and generating a satellite navigation signal affected by the ionospheric anomaly. The present invention can simulate and generate satellite navigation signals when ionospheric threats and ionospheric scintillation occur simultaneously, thereby enhancing the fidelity of the simulation of actual ionospheric anomaly scenarios. Application of this method improves the credibility of test results for satellite landing system receivers.

Description

Technical Field

[0001] The present invention relates to a satellite landing system receiver testing method, and in particular to an ionospheric anomaly simulation method for testing a satellite landing system receiver. Background Art

[0002] The Satellite Landing System (GLS) is an approach and landing system based on satellite navigation and the Ground-Based Augmentation System (GBAS). GLS comprises the GBAS system, which guides precision approaches and landings, and its associated aircraft functions. Using correction information broadcast by the GBAS ground subsystem, the onboard GLS receiver implements real-time differential corrections, enhancing navigation performance during approach and landing.

[0003] Satellite navigation systems offer global coverage and all-weather operation, providing real-time positioning, velocity measurement, and timing services. The International Civil Aviation Organization (ICAO) has designated China's Beidou Navigation Satellite System (BDS), the United States' Global Positioning System (GPS), Russia's GLONASS, and Europe's Galileo as the four major satellite navigation system providers. To provide global satellite navigation signals that meet the navigation performance requirements for different flight phases, ICAO has defined satellite navigation augmentation systems (ASAS), including airborne, ground-based, and satellite-based augmentation. These, combined with satellite navigation systems, form the Global Navigation Satellite System (GNSS). To ensure navigation performance in actual operations, the civil aviation industry has established minimum navigation performance requirements for GNSS receivers during different flight phases.

[0004] In the propagation path of satellite navigation signals, the ionosphere, as an inhomogeneous dispersive medium, affects the amplitude, phase, and delay information of satellite navigation signals, resulting in a degradation of the navigation performance of GNSS receivers. When the ionosphere is normal, the impact on satellite navigation signals can be corrected using ionospheric models, such as the Klobuchar model. When the ionosphere is abnormal, the impact on satellite navigation signals can be mitigated through dual-frequency reception, adaptive filtering, differential correction, and other methods. Testing whether GNSS receivers meet the corresponding minimum navigation performance requirements in different flight phases and ionospheric conditions is a key step in ensuring the safe application of GNSS receivers in civil aviation. The most stringent testing requirements are for GLS receivers operating during the approach and landing phases of flight. To achieve the purpose of this testing, a satellite navigation signal generator with ionospheric anomaly simulation capabilities is required.

[0005] According to the physical characteristics of ionospheric irregularities with ionization density higher or lower than the average ionization density of the surrounding medium, there are ionospheric anomaly models corresponding to irregularities of different scales: (1) Ionospheric threat models, which are used to simulate ionospheric delay anomalies caused by large-scale irregularities, including wedge models that simulate ionospheric delay anomalies under ionospheric storms and trapezoidal models that simulate ionospheric delay anomalies under plasma bubbles. These models are essentially linear models; (2) Ionospheric scintillation models, which are used to simulate ionospheric scintillation caused by small and medium-scale irregularities, including empirical models based on statistical probability and phase screen models based on spatial spectrum density. These models are essentially nonlinear models. At present, most satellite navigation signal generators with ionospheric anomaly simulation functions use ionospheric anomaly models based on the assumption of a single ionospheric thin shell, which can only simulate single ionospheric anomaly situations. For example, patent CN201710902331.8 proposes a phase screen-based method for simulating satellite navigation signals affected by ionospheric scintillation. This method imports the generated scintillation sequence into a normal satellite navigation signal to create a satellite navigation signal affected by ionospheric scintillation. However, research has shown that ionospheric threats and ionospheric scintillation can occur simultaneously during the approach and landing phase of flight. The above-mentioned method, which only simulates a single ionospheric anomaly, cannot reflect this situation. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide an ionospheric anomaly simulation method for satellite landing system receiver testing, which can enhance the fidelity of simulation of actual ionospheric anomaly conditions.

[0007] The technical solution adopted by the present invention is: an ionospheric anomaly simulation method for satellite landing system receiver testing, comprising the following steps:

[0008] 1) Setting the motion parameters for ionospheric anomaly situations. The ionospheric anomaly situation refers to situations where the satellite and aircraft velocity vectors are in the same direction, and ionospheric threats and ionospheric scintillation exist simultaneously, affecting the receiver.

[0009] 2) Setting relevant parameters of the ionospheric threat model, wherein the ionospheric threat model includes: a wedge model simulating ionospheric delay anomalies under ionospheric storms, and a trapezoidal model simulating ionospheric delay anomalies under plasma bubbles;

[0010] 3) setting parameters of an ionospheric anomaly space model based on relative motion, wherein the ionospheric anomaly space model is a model that describes the relative motion of an ionospheric scintillation model and an ionospheric threat model; wherein the ionospheric scintillation model adopts a double power-law phase screen model, and the ionospheric threat model adopts a wedge model or a trapezoidal model;

[0011] 4) setting phase screen model parameters, wherein the phase screen model parameters are parameters of a double power-law phase screen model, including: spectral indices p1, p2, and spectral break normalized wave number μ0;

[0012] 5) Generate satellite navigation signals affected by ionospheric anomalies. Based on the phase screen model and the ionospheric threat model, first generate satellite navigation digital intermediate frequency signals affected by ionospheric anomalies. Then, through digital-to-analog conversion and up-conversion, generate satellite navigation signals affected by ionospheric anomalies.

[0013] The present invention provides an ionospheric anomaly simulation method for testing satellite landing system receivers. This method considers the simultaneous presence of ionospheric threats and ionospheric scintillation, which may occur during the approach and landing phase and impact the receiver. Based on relative motion relationships, it analyzes the correlation between the ionospheric scintillation model and the ionospheric threat model parameters, and then establishes an ionospheric scintillation model parameter estimation model that affects satellite navigation signals. Based on this, it simulates and generates satellite navigation signals affected by ionospheric anomalies. The present invention can reproduce the complex ionospheric anomaly conditions experienced by the propagation path of satellite navigation signals and can simulate and generate satellite navigation signals when ionospheric threats and ionospheric scintillation occur simultaneously, thereby enhancing the fidelity of the simulation of actual ionospheric anomaly conditions. Application of this method improves the credibility of test results for satellite landing system receivers. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a flow chart of an ionospheric anomaly simulation method for satellite landing system receiver testing according to the present invention;

[0015] Figure 2 A wedge model for simulating ionospheric delay anomalies during ionospheric storms;

[0016] Figure 3 Trapezoidal model for simulating ionospheric delay anomalies under plasma bubbles;

[0017] Figure 4 Worst-case model for simultaneous occurrence of ionospheric storms and ionospheric scintillation;

[0018] Figure 5 Worst-case model for simultaneous occurrence of plasma bubbles and ionospheric scintillation;

[0019] Figure 6 Flowchart of the phase screen model parameter setting method based on relative motion. DETAILED DESCRIPTION

[0020] The following describes in detail an ionospheric anomaly simulation method for testing a satellite landing system receiver according to the present invention in conjunction with the embodiments and accompanying drawings.

[0021] like Figure 1 As shown, the present invention provides an ionospheric anomaly simulation method for satellite landing system receiver testing, comprising the following steps:

[0022] 1) Set the motion parameters for ionospheric anomaly situations;

[0023] The ionospheric anomaly situation refers to the situation where the satellite and aircraft velocity vectors are in the same direction and the ionospheric threat and ionospheric scintillation exist at the same time and affect the receiver;

[0024] The said setting of ionospheric anomaly motion parameters includes: ionospheric anomaly start time t1, nth satellite motion velocity vector v n,s , aircraft velocity vector v p , the height difference h between the nth satellite and the aircraft at the beginning of the ionospheric anomaly n,s , the height difference between the ionosphere and the aircraft h ion , the ionospheric puncture point motion velocity vector v of the nth satellite navigation signal n,IPP The ionospheric puncture point is the intersection of the line between the aircraft and the satellite and the ionospheric shell model; the motion velocity vector of the ionospheric puncture point is related to the motion parameters of other ionospheric anomalies:

[0025]

[0026] Among them, || is an operator for taking the magnitude of the motion velocity vector;

[0027] 2) Setting ionospheric threat model parameters;

[0028] According to the two ionospheric threat models specified by the International Civil Aviation Organization, the ionospheric threat models include: a wedge model that simulates ionospheric delay anomalies under ionospheric storms, and a trapezoidal model that simulates ionospheric delay anomalies under plasma bubbles. The relevant parameters of the ionospheric threat model are set; in the embodiment of the present invention, one of the two models can be selected as needed. Among them:

[0029] The wedge model used to simulate the ionospheric delay anomaly under ionospheric storms is as follows: Figure 2 As shown, first set the ionospheric threat model parameters that affect the navigation signal of the nth satellite: slope gradient g n,i , ramp gradient width w n,i , the maximum delay D of the wedge model n,i , ionospheric storm motion velocity vector v n,i The ionospheric storm velocity vector is in the same direction as the satellite and aircraft velocity vectors; the maximum delay D of the wedge model n,i With the slope gradient width w n,i , slope gradient g n,i The following relationship is satisfied:

[0030] D n,i =w n,i ·g n,i (2)

[0031] The trapezoidal model used to simulate the ionospheric delay anomaly under the plasma bubble is as follows: Figure 3 As shown, first set the ionospheric threat model parameters that affect the navigation signal of the nth satellite: forward slope gradient g n,f , forward ramp gradient width w n,f , backward slope gradient g n,a , backward slope gradient width w n,a , plasma bubble bottom width w n,u , the maximum delay D of the trapezoidal model n,b , plasma bubble velocity vector v n,b The velocity vector of the plasma bubble is in the same direction as the velocity vector of the satellite and the aircraft; the maximum delay D of the trapezoidal model n,b With the forward slope gradient width w n,f , forward slope gradient g n,f , backward slope gradient width w n,a , backward slope gradient g n,a The following relationship is satisfied:

[0032] D n,b =w n,f ·g n,f =w n,a ·g n,a (3)

[0033] There are two ways to obtain the ionospheric threat model parameter values: the first way is to use the regional worst-case ionospheric threat model published by the International Civil Aviation Organization; the second way is to use the regional worst-case ionospheric threat model published by the regional civil aviation regulatory agency. In this embodiment of the present invention, the first way is adopted.

[0034] 3) Setting the parameters of the ionospheric anomaly spatial model based on relative motion;

[0035] The ionospheric anomaly spatial model is a model that describes the relative motion of the ionospheric scintillation model and the ionospheric threat model; wherein the ionospheric scintillation model adopts a double power law phase screen model, and the ionospheric threat model adopts a wedge model or a trapezoidal model;

[0036] The parameters of the ionospheric anomaly space model include the duration T of the ionospheric anomaly, the relative motion distance d between the phase screen model affecting the nth satellite navigation signal and the ionospheric threat model. n , affecting the phase screen width w of the nth satellite navigation signal n,cThe duration of the ionospheric anomaly situation T, the relative motion distance d between the ionospheric scintillation model and the ionospheric threat model that affects the navigation signal of the nth satellite n It is set through the human-machine interface;

[0037] Based on the thin ionospheric shell hypothesis: The ionospheric free electrons that affect satellite navigation signals are theoretically concentrated in a very thin sphere. It is assumed that both ionospheric scintillation and ionospheric threats occur within the thin ionospheric shell. Therefore, the altitude difference between the ionospheric scintillation model and the ionospheric threat model and the aircraft is set to be equivalent to the altitude difference between the ionosphere and the aircraft.

[0038] The phase screen width w n,c The calculation process is as follows:

[0039] (3.1) When the ionospheric threat model in step 2) adopts the wedge model, proceed to step (3.2); when the ionospheric threat model in step 2) adopts the trapezoidal model, proceed to step (3.3);

[0040] (3.2) Calculate the phase screen width w that affects the nth satellite navigation signal when using the wedge model n,c ;

[0041] The worst-case model for the simultaneous occurrence of ionospheric storms and ionospheric scintillation is as follows: Figure 4 As shown in the figure, at the time t1 when the ionospheric anomaly begins, the ionospheric puncture point coincides with the front of the ionospheric storm front and the rear end of the phase screen that affect the navigation signal of the nth satellite; during the duration of the ionospheric anomaly, the ionospheric storm motion velocity vector v that affects the navigation signal of the nth satellite is n,i The magnitude is greater than the phase screen motion velocity vector v n,c After the ionospheric anomaly lasts for T, the front of the phase screen coincides with the ionospheric puncture point, and the distance between the front point of the ionospheric storm front and the rear end of the phase screen is d. n , that is, the relative motion distance between the phase screen model and the wedge model is d n .

[0042] Calculate the phase screen width w that affects the navigation signal of the nth satellite n,c The formula is as follows:

[0043]

[0044] At the same time, the phase screen width w that affects the nth satellite navigation signal n,c Size meets:

[0045] w n,c >d n -w n,i >0 (5)

[0046] Among them, vn,i is the ionospheric storm motion velocity vector; v p is the aircraft velocity vector; h n,s h is the height difference between the nth satellite and the aircraft at the beginning of the ionospheric anomaly; ion is the height difference between the ionosphere and the aircraft; v n,s is the velocity vector of the nth satellite; w n,i is the slope gradient width;

[0047] (3.3) Calculate the phase screen width w that affects the nth satellite navigation signal when using the trapezoidal model n,c ;

[0048] The worst-case model for the simultaneous occurrence of plasma bubbles and ionospheric scintillation is as follows: Figure 5 As shown in Figure 2. At the time t1 when the ionospheric anomaly begins, the ionospheric puncture point coincides with the front of the plasma bubble and the rear of the phase screen. During the duration of the ionospheric anomaly, the velocity vector v of the plasma bubble that affects the navigation signal of the nth satellite is n,b The magnitude is greater than the phase screen motion velocity vector v n,c After the ionospheric anomaly lasts for T, the front of the phase screen coincides with the ionospheric puncture point, and the distance between the front of the plasma bubble and the rear of the phase screen is d. n , that is, the relative motion distance between the phase screen model and the trapezoidal model is d n .

[0049] Calculate the phase screen width w that affects the navigation signal of the nth satellite n,c The formula is as follows:

[0050]

[0051] At the same time, the phase screen width w that affects the nth satellite navigation signal n,c Size meets:

[0052] w n,c >d n -(w f +w u +w a )>0 (7)

[0053] Among them, v n,b is the velocity vector of plasma bubble motion;

[0054] 4) Set the phase screen model parameters;

[0055] The phase screen model parameters are parameters of a double power-law phase screen model, including: spectrum indices p1, p2, and spectrum break normalized wave number μ0;

[0056] In order to control the statistical characteristics of the flashing sequence, the following Figure 6 The phase screen model parameter setting method based on relative motion is shown to indirectly set the spectrum indices p1, p2 and the spectrum break normalized wave number μ0.

[0057] like Figure 6 As shown, the phase screen model parameter setting method includes:

[0058] (4.1) Obtaining ionospheric anomaly parameters: ionospheric storm velocity vector v n,i , plasma bubble velocity vector v n,b , the duration of the ionospheric anomaly T, the width w of the phase screen affecting the navigation signal of the nth satellite n,c , the relative motion distance d between the phase screen model and the ionospheric threat model that affect the nth satellite navigation signal n ;

[0059] (4.2) Obtain ionospheric scintillation observation data: including phase scintillation index σ 2 and amplitude flicker index S 2 ; The observation period of ionospheric scintillation observation data is 60s. There are two methods for obtaining ionospheric scintillation observation data: the first is to obtain it through a scintillation monitor device, and the second is to obtain it through a historical scintillation index data database provided by the ionospheric observation network; the embodiment of the present invention can be obtained using a historical scintillation index data database.

[0060] (4.3) Divide the ionospheric scintillation observation data into blocks: divide each ionospheric anomaly duration T into a data block;

[0061] (4.4) Estimating the phase screen model parameters: Based on the amplitude space spectral density function, a cost function for estimating the phase screen model parameters is constructed, and the phase screen model parameters are obtained by minimizing the cost function;

[0062] The minimization cost function is the cost function for the ionospheric scintillation spectrum index p 1,n (k), p 2,n (k), spectrum break normalized wave number μ 0,n (k) Estimated cost function J n (k) Minimize:

[0063]

[0064] Where k represents the sequence number of the observation data point in the current observation data block, n is the satellite sequence number; J n (k) represents the estimated cost function of the phase screen model parameters of the n-th satellite navigation signal in the k-th observation data point; are the ionospheric amplitude scintillation index and phase scintillation index of the nth satellite navigation signal at the kth observation data point; μ is the normalized wave number, μ c,n (k), μ d,n (k) are the lower and upper cutoff normalized wave numbers of the bandpass filter required to calculate the amplitude scintillation index of the n-th satellite navigation signal at the k-th observation data point; p 1,n (k), p 2,n (k) is the ionospheric scintillation spectrum index of the nth satellite navigation signal at the kth observation data point, μ 0,n (k) is the normalized wave number of the ionospheric scintillation spectrum of the n-th satellite navigation signal at the k-th observation data point; I n () is the amplitude space spectral density function of the double power-law phase screen model;

[0065] The minimization is based on p 1,n (k), p 2,n (k), μ 0,n (k) is the independent variable. Using numerical integration algorithm and minimization search method, we can solve the minimization formula (8) to obtain p 1,n (k), p 2,n (k), μ 0,n The value of (k) constitutes the phase screen model parameter. In the embodiment of the present invention, the numerical integration algorithm uses the Gaussian integration method, and the minimization search method uses the gradient descent method.

[0066] 5) Generate satellite navigation signals affected by ionospheric anomalies.

[0067] Based on the phase screen model and the ionospheric threat model, the digital intermediate frequency signal of satellite navigation affected by ionospheric anomalies is first generated. Then, through digital-to-analog conversion and up-conversion, the satellite navigation signal affected by ionospheric anomalies is generated.

[0068] The satellite navigation digital intermediate frequency signal affected by the ionospheric anomaly is:

[0069] s n,k (m)=[A n,k (m)δA n,k (m)D n,k (m)C n,k (m)cos n,k (m)]+ε n,k (m) (9)

[0070]

[0071]

[0072]

[0073] Where k represents the sequence number of the observation data point in the current observation data block, n is the satellite sequence number, m is the sampling sequence number within the kth observation data point, Δt i is the sampling period of the satellite navigation digital intermediate frequency signal. n,k (m) is the navigation digital intermediate frequency signal of the nth satellite at the mth sampling point in the kth observation data point; A n,k (m) is the amplitude of the navigation digital intermediate frequency signal of the nth satellite at the mth sampling point in the kth observation data point, which is set through the human-machine interface; cos n,k (m) is the carrier of the navigation digital intermediate frequency signal of the nth satellite at the mth sampling point in the kth observation data point; C n,k (m) and D n,k (m) are the spreading code and navigation message of the navigation digital intermediate frequency signal of the nth satellite at the mth sampling point in the kth observation data point. The spreading code and navigation message are specified by the satellite navigation system standard; n,k (m) is the random noise of the nth satellite at the mth sampling point in the kth observation data point, which is modeled using white noise; f i is the intermediate frequency of the satellite navigation digital intermediate frequency signal; Γ n,k (m), are the pseudo code delay sequence and phase delay sequence of the navigation digital intermediate frequency signal of the nth satellite at the mth sampling point in the kth observation data point under normal circumstances, respectively, which are set according to the satellite navigation system standard; δA n,k (m), are the amplitude scintillation sequence and phase scintillation sequence of the navigation digital intermediate frequency signal of the nth satellite at the mth sampling point in the kth observation data point under the influence of ionospheric anomaly, τ n,k (m), ξ n,k (m) are the pseudo code delay sequence and phase delay sequence of the navigation digital intermediate frequency signal of the nth satellite at the mth sampling point in the kth observation data point under the influence of ionospheric anomaly; is the floor operator. D n is the navigation message of the nth satellite; C n is the spreading code of the nth satellite;

[0074] In the embodiment of the present invention, the observation period is 60s, the effective duration of the flashing sequence and the delay sequence is 60s; the sampling period Δt of the satellite navigation digital intermediate frequency signal is i Take 0.1μs, intermediate frequency f i Take 2.5MHz; at each observation data point, the length of the satellite navigation digital intermediate frequency signal is M i =60 / Δt i .

[0075] The amplitude scintillation sequence and phase scintillation sequence under the influence of ionospheric anomaly are based on the phase screen theory and are generated by the following steps:

[0076] (a) Calculation of phase screen response function: The double power-law phase screen model parameters obtained in step 4) are: p 1,n (k), p 2,n (k), μ 0,n The value of (k) is substituted into the phase space spectrum density function of the double power law phase screen model, and the phase space spectrum density function is subjected to step-by-step discrete Fourier transform to obtain the phase screen response function;

[0077] (b) Free propagation process realization: Perform a step-by-step discrete Fourier transform on the phase screen response function to obtain the complex signal that reaches the receiver antenna after passing through the phase screen and undergoing a free propagation process;

[0078] (c) Scintillation sequence generation: The complex signal is processed by conjugate modulo, arc tangent, jump correction and interpolation to obtain the amplitude scintillation sequence δA under the influence of ionospheric anomalies. n,k (m) and phase scintillation sequences

[0079] The interpolation process is to interpolate the flicker sequence generated after the jump correction. The sampling period of the flicker sequence after the jump correction is Δt s , taking 0.001~1s, the embodiment of the present invention can take 0.01s, the flashing sequence length is M sci =60 / Δt sci In generating satellite navigation digital intermediate frequency signals affected by ionospheric anomalies, the scintillation sequence must be consistent with the sampling period of the satellite navigation digital intermediate frequency signal. Interpolation processing is required on the generated scintillation sequence. The interpolation method used is Lagrange interpolation, Newton interpolation, or third-order spline interpolation. In embodiments of the present invention, the third-order spline interpolation method may be used.

[0080] The pseudo code delay sequence and phase delay sequence under the influence of ionospheric anomaly are generated according to the selection of the ionospheric threat model, as follows:

[0081] (d) When the ionospheric threat model in step 2) adopts a wedge model, proceed to step (e); when the ionospheric threat model in step 2) adopts a trapezoidal model, proceed to step (f);

[0082] (e) Based on the wedge model parameters, calculate the pseudo-code delay sequence τ caused by the ionospheric storm during the duration of the ionospheric anomaly. n,k (m):

[0083]

[0084] Where k represents the sequence number of the observation data point in the current observation data block, n is the satellite sequence number, m is the sampling sequence number within the kth observation data point, Δt i is the sampling period of the satellite navigation digital intermediate frequency signal; d n is the relative motion distance between the phase screen model and the wedge model, w n,c is the phase screen width; D n,i is the maximum delay of the wedge model, w n,i is the slope gradient width, g n,i is the slope gradient; c is the speed of light; T is the duration of the ionospheric anomaly.

[0085] Phase delay sequence ξ caused by ionospheric storm during the duration of ionospheric anomaly n,k (m) is calculated by the following formula:

[0086]

[0087] Among them, λ e The signal wavelength of the band used for satellite navigation signals;

[0088] (f) Calculate the pseudo-code delay sequence τ caused by the plasma bubble during the duration of the ionospheric anomaly based on the trapezoidal model parameters. n,k (m):

[0089]

[0090] Where k represents the sequence number of the observation data point in the current observation data block, n is the satellite sequence number, m is the sampling sequence number within the kth observation data point, Δt i is the sampling period of the satellite navigation digital intermediate frequency signal; d n is the relative motion distance between the phase screen model and the wedge model, w n,c is the phase screen width; D n,b is the maximum delay of the trapezoidal model, g n,f is the forward slope gradient, w n,f is the forward ramp gradient width, g n,a is the backward slope gradient, w n,a is the width of the backward slope gradient, w n,u is the bottom width of the plasma bubble; c is the speed of light; T is the duration of the ionospheric anomaly.

[0091] Phase delay sequence ξ caused by plasma bubbles during the duration of ionospheric anomalies n,k (m) is calculated by the following formula:

[0092]

[0093] Among them, λ eThe signal wavelength of the band used for satellite navigation signals.

Claims

1. A method for simulating ionospheric anomalies for satellite landing system receiver testing, characterized in that: The steps include: 1) Set the motion parameters for ionospheric anomaly situations. The ionospheric anomaly situation refers to situations where the satellite and aircraft velocity vectors are in the same direction, and ionospheric threats and ionospheric scintillation exist simultaneously, affecting the receiver. 2) Setting relevant parameters of the ionospheric threat model, wherein the ionospheric threat model includes: a wedge model simulating ionospheric delay anomalies under ionospheric storms, and a trapezoidal model simulating ionospheric delay anomalies under plasma bubbles; 3) Setting parameters of an ionospheric anomaly space model based on relative motion, wherein the ionospheric anomaly space model is a model that describes the relative motion of the ionospheric scintillation model and the ionospheric threat model; wherein the ionospheric scintillation model adopts a double power-law phase screen model, and the ionospheric threat model adopts a wedge model or a trapezoidal model; 4) Setting phase screen model parameters, which are parameters of a double-power-law phase screen model, including spectral indices p1 and p2, and spectral break normalized wave number μ0; 5) Generate satellite navigation signals affected by ionospheric anomalies. Based on the phase screen model and the ionospheric threat model, first generate a digital intermediate frequency signal of satellite navigation affected by ionospheric anomalies. Then, through digital-to-analog conversion and up-conversion, generate a satellite navigation signal affected by ionospheric anomalies.

2. The ionospheric anomaly simulation method for satellite landing system receiver testing according to claim 1, characterized in that: Step 1) The setting of the motion parameters of the ionospheric anomaly situation includes: the starting time t1 of the ionospheric anomaly situation, the motion velocity vector v of the nth satellite n,s , aircraft velocity vector v p , the height difference h between the nth satellite and the aircraft at the beginning of the ionospheric anomaly n,s , the height difference between the ionosphere and the aircraft h ion , the ionospheric penetration point motion velocity vector v of the nth satellite navigation signal n,IPP ; The velocity vector of the ionospheric puncture point is related to the motion parameters of other ionospheric anomalies: (1)； Among them, || is an operator for obtaining the magnitude of the motion velocity vector.

3. The ionospheric anomaly simulation method for satellite landing system receiver testing according to claim 1, characterized in that: Step 2) sets the relevant parameters of the ionospheric threat model, where: For the wedge model used to simulate the ionospheric delay anomaly under ionospheric storm, first set the ionospheric threat model parameters that affect the navigation signal of the nth satellite: the slope gradient g n,i , ramp gradient width w n,i , the maximum delay D of the wedge model n,i , ionospheric storm motion velocity vector v n,i The ionospheric storm velocity vector is in the same direction as the satellite and aircraft velocity vectors; the maximum delay D of the wedge model n,i With the slope gradient width w n,i , slope gradient g n,i The following relationship is satisfied: (2)； For the trapezoidal model used to simulate the ionospheric delay anomaly under the plasma bubble, first set the ionospheric threat model parameters that affect the navigation signal of the nth satellite: forward slope gradient g n,f , forward ramp gradient width w n,f , backward slope gradient g n,a , backward slope gradient width w n,a , plasma bubble bottom width w n,u , the maximum delay D of the trapezoidal model n,b , plasma bubble velocity vector v n,b ; The velocity vector of the plasma bubble is in the same direction as the velocity vector of the satellite and the aircraft; the maximum delay D of the trapezoidal model n,b With the forward slope gradient width w n,f , forward slope gradient g n,f , backward slope gradient width w n,a , backward slope gradient g n,a The following relationship is satisfied: (3)； There are two ways to obtain the values ​​of the ionospheric threat model parameters: the first way is the regional worst-case ionospheric threat model published by the International Civil Aviation Organization; the second way is the regional worst-case ionospheric threat model published by the regional civil aviation regulatory agency.

4. The ionospheric anomaly simulation method for satellite landing system receiver testing according to claim 1, characterized in that: The ionospheric anomaly spatial model parameters mentioned in step 3) include the duration T of the ionospheric anomaly, the relative motion distance d between the phase screen model affecting the nth satellite navigation signal and the ionospheric threat model. n , affecting the phase screen width w of the nth satellite navigation signal n,c The duration of the ionospheric anomaly situation T, the relative motion distance d between the ionospheric scintillation model and the ionospheric threat model that affects the navigation signal of the nth satellite n It is set through the human-machine interface; and the height difference between the ionospheric scintillation model and the ionospheric threat model and the aircraft is set to be equivalent to the height difference between the ionosphere and the aircraft.

5. The ionospheric anomaly simulation method for satellite landing system receiver testing according to claim 4, characterized in that: The phase screen width w n,c The calculation process is as follows: (3.1) When the ionospheric threat model in step 2) adopts the wedge model, proceed to step (3.2); when the ionospheric threat model in step 2) adopts the trapezoidal model, proceed to step (3.3); (3.2) Calculate the phase screen width w that affects the nth satellite navigation signal when using the wedge model n,c ; Calculate the phase screen width w that affects the navigation signal of the nth satellite n,c The formula is as follows: (4)； At the same time, the phase screen width w that affects the nth satellite navigation signal n,c Size meets: (5)； Among them, v n,i is the ionospheric storm motion velocity vector; v p is the aircraft velocity vector; h n,s h is the height difference between the nth satellite and the aircraft at the beginning of the ionospheric anomaly; ion is the height difference between the ionosphere and the aircraft; v n,s is the velocity vector of the nth satellite; w n,i is the slope gradient width; | | is the operator for taking the magnitude of the motion velocity vector; (3.3) Calculate the phase screen width w that affects the nth satellite navigation signal when using the trapezoidal model n,c ; Calculate the phase screen width w that affects the navigation signal of the nth satellite n,c The formula is as follows: (6)； At the same time, the phase screen width w that affects the nth satellite navigation signal n,c Size meets: (7)； Among them, v n,b is the velocity vector of plasma bubble, w n,f is the forward slope gradient width, w n,u is the bottom width of the plasma bubble, w n,a is the backward slope gradient width.

6. The ionospheric anomaly simulation method for satellite landing system receiver testing according to claim 1, characterized in that: The method for setting the phase screen model parameters described in step 4) includes: (4.1) Obtaining ionospheric anomaly parameters: ionospheric storm velocity vector v n,i , plasma bubble velocity vector v n,b , the duration of the ionospheric anomaly T, the width w of the phase screen affecting the navigation signal of the nth satellite n,c , the relative motion distance d between the phase screen model and the ionospheric threat model that affect the nth satellite navigation signal n ; (4.2) Obtaining ionospheric scintillation observation data: including phase scintillation index 2 and amplitude flicker index S 2 The observation period of ionospheric scintillation observation data is 60 seconds. There are two ways to obtain ionospheric scintillation observation data: the first is to obtain it through scintillation monitoring equipment, and the second is to obtain it through the historical scintillation index data database provided by the ionospheric observation network; (4.3) Divide the ionospheric scintillation observation data into blocks: divide the data into blocks every time the duration T of the ionospheric anomaly occurs; (4.4) Estimation of phase screen model parameters: Based on the amplitude space spectral density function, a cost function for estimating the phase screen model parameters is constructed. The phase screen model parameters are obtained by minimizing the cost function. The minimization cost function is the cost function for the ionospheric scintillation spectrum index p 1,n (k), p 2,n (k), spectrum break normalized wave number μ 0,n (k) Estimated cost function J n (k) Minimize: (8)； Where k is the sequence number of the observation data point in the current observation data block, n is the satellite sequence number; J n (k) represents the estimated cost function of the phase screen model parameters of the n-th satellite navigation signal in the k-th observation data point; 、 are the ionospheric amplitude scintillation index and phase scintillation index of the nth satellite navigation signal at the kth observation data point; μ is the normalized wave number, μ c,n (k), μ d,n (k) are the lower and upper cutoff normalized wave numbers of the bandpass filter required to calculate the amplitude scintillation index of the n-th satellite navigation signal at the k-th observation data point; p 1,n (k), p 2,n (k) is the ionospheric scintillation spectrum index of the nth satellite navigation signal at the kth observation data point, μ 0,n (k) is the normalized wave number of the ionospheric scintillation spectrum of the n-th satellite navigation signal at the k-th observation data point; I n ( ) is the amplitude space spectral density function of the double power-law phase screen model; The minimization is based on p 1,n (k), p 2,n (k), μ 0,n (k) is the independent variable. Using numerical integration algorithm and minimization search method, we can solve the minimization formula (8) to obtain p 1,n (k), p 2,n (k), μ 0,n The value of (k) constitutes the phase screen model parameter.

7. The ionospheric anomaly simulation method for satellite landing system receiver testing according to claim 6, characterized in that: The satellite navigation digital intermediate frequency signal affected by the ionospheric anomaly described in step 5) is: (9)； (10)； (11)； (12)； Among them, k is the sequence number of the observation data point in the current observation data block, n is the satellite sequence number; m is the sampling sequence number within the kth observation data point, Δt i is the sampling period of the satellite navigation digital intermediate frequency signal; s n,k (m) is the navigation digital intermediate frequency signal of the nth satellite at the mth sampling point in the kth observation data point; A n,k (m) is the amplitude of the navigation digital intermediate frequency signal of the nth satellite at the mth sampling point in the kth observation data point, which is set through the human-machine interface; cos n,k (m) is the carrier of the navigation digital intermediate frequency signal of the nth satellite at the mth sampling point in the kth observation data point; C n,k (m) and D n,k (m) are the spreading code and navigation message of the navigation digital intermediate frequency signal of the nth satellite at the mth sampling point in the kth observation data point. The spreading code and navigation message are specified by the satellite navigation system standard; n,k (m) is the random noise of the nth satellite at the mth sampling point in the kth observation data point, which is modeled using white noise; f i is the intermediate frequency of the satellite navigation digital intermediate frequency signal; n,k (m), φ n,k (m) are the pseudo code delay sequence and phase delay sequence of the navigation digital intermediate frequency signal of the nth satellite at the mth sampling point in the kth observation data point under normal circumstances, which are set according to the satellite navigation system standard; δA n,k (m), δφ n,k (m) are the amplitude scintillation sequence and phase scintillation sequence of the navigation digital intermediate frequency signal of the nth satellite at the mth sampling point in the kth observation data point under the influence of ionospheric anomaly, τ n,k (m),ξ n,k (m) are the pseudo code delay sequence and phase delay sequence of the navigation digital intermediate frequency signal of the nth satellite at the mth sampling point in the kth observation data point under the influence of ionospheric anomaly; D is the floor operator; n is the navigation message of the nth satellite; C n is the spreading code of the nth satellite.

8. The ionospheric anomaly simulation method for satellite landing system receiver testing according to claim 7, characterized in that: The amplitude scintillation sequence and phase scintillation sequence under the influence of ionospheric anomaly are based on the phase screen theory and are generated by the following steps: (a) Calculation of phase screen response function: The double power-law phase screen model parameters obtained in step 4) are: 1,n (k), p 2,n (k), μ 0,n The value of (k) is substituted into the phase space spectrum density function of the double power law phase screen model, and the phase space spectrum density function is subjected to step-by-step discrete Fourier transform to obtain the phase screen response function; (b) Free propagation process implementation: Perform a step-by-step discrete Fourier transform on the phase screen response function to obtain the complex signal that reaches the receiver antenna after passing through the phase screen and undergoing a free propagation process. (c) Scintillation sequence generation: The complex signal is processed by conjugate modulo, arc tangent, jump correction and interpolation to obtain the amplitude scintillation sequence δA under the influence of ionospheric anomalies. n,k (m) and phase scintillation sequence δφ n,k (m); The interpolation process is to interpolate the flicker sequence generated after the jump correction; The sampling period of the flicker sequence after jump correction is Δt s , take 0.001~1s, the flashing sequence length is M sci =60 / Δt sci ; In the generation of satellite navigation digital intermediate frequency signals affected by ionospheric anomalies, it is required that the scintillation sequence is consistent with the sampling period of the satellite navigation digital intermediate frequency signal, and the generated scintillation sequence is interpolated. The interpolation method used in the interpolation processing is Lagrange interpolation method, Newton interpolation method or third-order spline interpolation method.

9. The ionospheric anomaly simulation method for satellite landing system receiver testing according to claim 7, characterized in that: The pseudo code delay sequence and phase delay sequence under the influence of ionospheric anomaly are generated according to the selection of the ionospheric threat model, as follows: (d) When the ionospheric threat model in step 2) adopts a wedge model, proceed to step (e); when the ionospheric threat model in step 2) adopts a trapezoidal model, proceed to step (f); (e) Based on the wedge model parameters, calculate the pseudo-code delay sequence τ caused by the ionospheric storm during the duration of the ionospheric anomaly n,k (m): (13)； Among them, k represents the sequence number of the observation data point in the current observation data block, n is the satellite sequence number; m is the sampling sequence number within the kth observation data point, Δt i is the sampling period of the satellite navigation digital intermediate frequency signal; d n is the relative motion distance between the phase screen model and the wedge model, w n,c is the phase screen width; D n,i is the maximum delay of the wedge model, w n,i is the slope gradient width, g n,i is the slope gradient; c is the speed of light; T is the duration of the ionospheric anomaly; Phase delay sequence ξ caused by ionospheric storm during the duration of ionospheric anomaly n,k (m) is calculated by the following formula: (14)； Among them, λ e The signal wavelength of the band used for satellite navigation signals; (f) Based on the trapezoidal model parameters, calculate the pseudo-code delay sequence τ caused by the plasma bubble during the duration of the ionospheric anomaly n,k (m): (15)； Among them, k represents the sequence number of the observation data point in the current observation data block, n is the satellite sequence number; m is the sampling sequence number within the kth observation data point, Δt i is the sampling period of the satellite navigation digital intermediate frequency signal; d n is the relative motion distance between the phase screen model and the wedge model, w n,c is the phase screen width; D n,b is the maximum delay of the trapezoidal model, g n,f is the forward slope gradient, w n,f is the forward ramp gradient width, g n,a is the backward slope gradient, w n,a is the width of the backward slope gradient, w n,u is the bottom width of the plasma bubble; c is the speed of light; T is the duration of the ionospheric anomaly; Phase delay sequence ξ caused by plasma bubbles during the duration of ionospheric anomalies n,k (m) is calculated by the following formula: (16)； Among them, λ e The signal wavelength of the band used for satellite navigation signals.

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