A method for monitoring the integrity of an inertial / radar system for ship landing

Abstract

This invention discloses a method for monitoring the integrity of an inertial / radar system for shipboard landing. Based on the presence or absence of a fault, the total integrity risk is divided into fault-free integrity risk and integrity risk based on a fault detection mode. According to integrity index requirements, the probability of misleading information under each risk type is set. A filtered state equation model is established, and a measurement equation model is further set. Based on the measurements output from the measurement equation model and combined with the probability of misleading information under each risk type, the integrity level protection threshold (HPL) under fault-free conditions is calculated. FF Based on the measurements output from the measurement equation model, and combined with the probability of misleading information under each risk type, the integrity level protection threshold (HPL) under fault detection mode is calculated. FD According to HPL FF HPL FD The integrity protection level of the inertial / satellite combined output parameters is calculated. In the precision ship landing phase, where the accident rate is highest, the system can output the horizontal protection threshold under this scheme based on the confidence index required for the scenario.

Description

Technical Field

[0001] This invention belongs to the field of integrated navigation integrity technology, specifically relating to a method for monitoring the integrity of an inertial / radar system for ship landing. Background Technology

[0002] Precision landing is the stage with the highest accident rate. Statistics show that approximately 80% of carrier-based aircraft accidents occur during landing; therefore, ensuring the reliability of the landing process is one of the key technologies for achieving precision landing. Given that satellite navigation radar is a crucial component of the shipborne air navigation system, it plays an irreplaceable role in guiding carrier-based aircraft to safe landings. The landing guidance radar measures the aircraft's relative position information in real time, including azimuth, elevation angle, and distance, and transmits this information wirelessly to takeoff and landing guidance command facilities. Inertial / radar-based integrated navigation can compensate for dangerous scenarios where RTK relative positioning fails in a no-address environment, thus failing to provide accurate relative positioning for landing.

[0003] Radar ranging and direction finding accuracy is easily affected by atmospheric conditions, synchronization errors, spot coincidence accuracy, and antenna height; it is also susceptible to interference from other surrounding signal sources, such as power lines, buildings, and radio equipment. Therefore, the integrity of the inertial / radar system should be monitored in real time during ship landing, and an alarm should be triggered promptly in case of malfunction. Summary of the Invention

[0004] The purpose of this invention is to provide an integrity monitoring method for shipboard inertial / radar integrated navigation, which realizes the confidence index required by the scenario, outputs the horizontal protection threshold under the scheme, and promptly alarms when the position error exceeds the threshold, thus ensuring the integrity of the system.

[0005] The technical solution of this invention: In order to achieve the above-mentioned objective, a method for monitoring the integrity of an inertial / radar combination during ship landing is proposed, comprising the following steps:

[0006] Step 1: Based on the presence or absence of faults, the total integrity risk is divided into fault-free integrity risk and integrity risk based on fault detection mode;

[0007] Step 2: Based on the integrity requirements of the inertial / radar integrated navigation system, set the probability of dangerous misleading information under each risk type in Step 1, and denot it as the probability of fault-free dangerous misleading information PHMI. FF and Probability of Misleading Fault Detection Information (PHMI) FD ;

[0008] Step 3: Establish a filtered state equation model for the ship-oriented inertial / radar integrated navigation system, and further set up the measurement equation model;

[0009] Step 4: Based on the measurements output from the measurement equation model in Step 3, and combined with the probability of misleading information under each risk type in Step 2, calculate the integrity level protection threshold (HPL) under fault-free conditions. FF ;

[0010] Step 5: Based on the measurements output from the measurement equation model in Step 3, and combined with the probability of misleading information under each risk type in Step 2, calculate the integrity level protection threshold (HPL) under the fault detection mode. FD ;

[0011] Step 6: Based on the fault-free integrity level protection threshold HPL obtained in Step 4. FF The integrity level protection threshold (HPL) obtained in step 5 under the fault detection mode FD The integrity protection level of the inertial / satellite combined output parameters is calculated using the following formula:

[0012] HPL F =max(HPL) GNSS HPL H0 HPL FD )

[0013] HPL GNSS The horizontal protection threshold for satellite space signals is transmitted from the outside.

[0014] In one possible embodiment, the specific process of establishing the filtered state equation model of the ship-oriented inertial / radar integrated navigation system in step 3 includes:

[0015] The state variables of the inertial navigation system in the Earth coordinate system e are defined as follows:

[0016]

[0017] Wherein, δP e For the 3D position error in the e-frame, δV e For the 3D velocity error in the e-frame, For 3D attitude misalignment angle error, δb a For 3D accelerometer zero bias, δb g Zero bias for 3D gyroscope;

[0018] The filter state equation model for the inertial / radar integrated navigation system is as follows:

[0019]

[0020] Next, a time update is performed, and the state is predicted in one step according to the following formula: X. k / k-1 One-step prediction mean square error matrix P k / k-1 :

[0021] X K / K-1 =φ K / K-1 ·X K-1

[0022]

[0023] Wherein, the noise parameter matrix Q K-1 Based on the system noise matrix, specific values ​​can be set according to the actual situation.

[0024] In one possible embodiment, step 3, the specific process of setting the measurement equation model includes:

[0025] Based on the state update results, perform measurement updates:

[0026] Let L D , λ D h D For the latitude, longitude, and altitude of the radar ranging station, L ψ , λ ψ h ψ For the latitude, longitude, and altitude of the radar azimuth station, L θ , λ θ h θ For the radar altitude station's latitude, longitude, and altitude; ρ D ,ψ D ,θ D These are the radar measurement parameters: slant range, azimuth, and elevation.

[0027] The latitude, longitude, and altitude of a radar ranging station can be converted to a fixed rectangular coordinate system using the following formula:

[0028] Find the coordinates of the radar ranging station in the Earth's fixed rectangular coordinate system:

[0029]

[0030] Determine the coordinates of the radar azimuth station in a fixed rectangular coordinate system on Earth:

[0031]

[0032] Determine the coordinates of the radar elevation station in a fixed rectangular coordinate system:

[0033]

[0034] Among them, R N Let be the Earth's radius, and e be the Earth's eccentricity.

[0035] Calculate the corrected inertial navigation position:

[0036] Lat = Lat_ins-X INS_k / k-1[1]

[0037] Lon = Lon_ins-X INS_k / k-1 [2]

[0038] height = hX INS_k / k-1 [3]

[0039] Among them, X INS_k / k-1 As a one-step state transition variable, Lat_ins is the local latitude calculated by the inertial system, Lon_ins is the local longitude calculated by the inertial system, and h is the inertial atmospheric damping height; the corrected inertial navigation position is transformed from the geographic coordinate system to the Earth's fixed rectangular coordinate system:

[0040] x=(R N +height)cos(Lat)cos(Lon)

[0041] y = (R) N +height)cos(Lat)sin(Lon)

[0042] z = [R] N (1-e 2 )+height]sin(Lat)

[0043] Based on the corrected inertial navigation position (x, y, z) and station position (x, y, z) in the above fixed rectangular coordinate system. D ,y D ,z D The intermediate distance measurement is calculated using the following formula:

[0044]

[0045] in,

[0046] Calculate the intermediate azimuth measurement using the following formula:

[0047]

[0048] in,

[0049] Calculate the intermediate height measurement using the following formula:

[0050]

[0051] in, Based on the intermediate measurements in the above steps, the equivalent measurement is calculated as follows:

[0052] Calculate the equivalent slope distance based on intermediate measurements during distance measurement:

[0053]

[0054] Calculate the equivalent azimuth angle ψ based on intermediate azimuth measurements. C :

[0055]

[0056] In the above formula, Δλ=Lon-λ ψ ;

[0057] Calculate the equivalent elevation angle based on the intermediate azimuth measurement:

[0058]

[0059] In summary, the calculation equation is as follows:

[0060]

[0061] The measurement transition matrix is ​​calculated as follows:

[0062]

[0063] The B matrix is ​​calculated using the corrected inertial navigation positions Lat, Lon, and height.

[0064]

[0065] Substituting the above calculation results into the first 3×3 dimensions of the Hk matrix (a 3*state number) dimension matrix, H... k The remaining elements are 0;

[0066] R k The parameters of the matrix are determined based on the actual situation;

[0067] Based on this, the covariance P of the measurement update results is calculated. k and state estimation X K :

[0068]

[0069] X K =X K / K-1 +K K ·Z K

[0070]

[0071] Among them, K K R is the filter gain coefficient. K This is the measurement noise matrix.

[0072] In one possible embodiment, step 4 specifically includes the following steps:

[0073] Step 4.1 Calculate the attitude projection matrix from the Earth-centered Earth-fixed coordinate system (ECEF) to the navigation system. Then, the projection of the filter covariance in step 3 onto the N-system is obtained:

[0074]

[0075] in, The calculation method is as follows:

[0076]

[0077] Among them, R N Where is the Earth's radius, e is the Earth's eccentricity, Lat is the local latitude, and Lon is the local longitude;

[0078] The converted inertial / radar combined filter Pk N Calculate the largest eigenvalue of the covariance matrix:

[0079]

[0080] Step 4.2 Calculate the level of protection under the fault-free integrity risk assumption based on the largest eigenvalue of the covariance matrix:

[0081]

[0082] Among them, K FF Based on PHMI FF The calculation is based on the Rayleigh distribution's confidence interval, as follows:

[0083] K FF =raylinv(1-PHMI) FF ).

[0084] In one possible embodiment, step 5 specifically includes the following steps:

[0085] Step 5.1 Calculate the measurement residual: r K =Z K -H k X k / k-1

[0086] Step 5.2 Based on Step 5.1, perform fault detection analysis:

[0087] When there are no faults, r K =Z K -H k X k / k-1 It follows a normal distribution N(0,A) with zero mean K ), where A K The variance of the normal distribution is calculated as follows:

[0088] A K =H K P K (H K ) T +R K

[0089] Step 5.3 For each dimension of the measurement residual r i Construct the detection function λ i =r i T r i Its detection threshold D i for:

[0090] D i =K FA *sqrt(A kii )

[0091] Where K FA The false alarm rate (PML) index for radar faults is determined by the system, and the specific calculation method is as follows:

[0092] K FAi =Q -1 (1-P ml i)

[0093] Projecting Di onto the geographic coordinate system, we get D H .

[0094] Step 5.4 then determines the horizontal detection threshold:

[0095]

[0096] Step 5.5, based on Step 5.4, determines the integrity protection level:

[0097] HPL FD The detection threshold for residual detection is calculated based on the combined inertial / radar detection capability and projected onto the geographic coordinate system.

[0098] Calculate the integrity protection level:

[0099] HPL FD =D H +K Hmd σ H

[0100] Among them, K Hmd =raylinv(1-PHMI) FD i)

[0101] σ H This is the 1σ value of the horizontal error of the inertial / radar combination.

[0102] According to a second aspect of the present invention, an inertial / radar system integrity monitoring device for ship landing is provided, for implementing the aforementioned inertial / radar system integrity monitoring method for ship landing, characterized in that it includes: a filter state equation model construction unit for an inertial / radar integrated navigation system, used to establish a filter state equation model for a ship landing-oriented inertial / radar integrated navigation system; a measurement equation model construction unit, used to further set a measurement equation model based on the filter state equation model for a ship landing-oriented inertial / radar integrated navigation system; and a fault-free integrity level protection threshold calculation unit, used to calculate the fault-free integrity level protection threshold HPL based on the measurements output by the measurement equation model and the probability of misleading information under various risk types. FF The integrity level protection threshold calculation unit in fault detection mode is used to calculate the integrity level protection threshold (HPL) in fault detection mode based on the measurements output from the measurement equation model and the probability of misleading hazard information under each risk type. FD Inertial / satellite integrated inertial navigation system integrity protection level calculation unit, used to calculate the integrity protection level (HPL) of the inertial / satellite integrated inertial navigation system. GNSS .

[0103] According to a third aspect of the present invention, a computer storage medium is provided, which stores a computer program that, when executed by a processor, implements the above-described method for monitoring the integrity of an inertial / radar combination for shipboard landing.

[0104] According to a fourth aspect of the invention, a computer program product containing instructions is provided, which, when run on a computer, causes the computer to execute the above-described method for monitoring the integrity of an inertial / radar combination for shipboard landing.

[0105] The beneficial technical effects of this invention are as follows: This invention provides an integrity monitoring method for inertial / radar integrated navigation for ship landing. In the precision ship landing process, where the accident rate is highest, it can realize the confidence index required by the scenario, output the horizontal protection threshold under this scheme, and promptly alarm when the position error exceeds the threshold. This avoids introducing erroneous information into the ship landing process and causing safety risks when the radar ranging and direction finding accuracy is affected by adverse external factors and interference from other surrounding signal sources. Attached Figure Description

[0106] Figure 1 Flowchart of a preferred embodiment of the present invention;

[0107] Figure 2 This is a detailed step diagram of a preferred embodiment of the present invention. Detailed Implementation

[0108] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0109] The features and illustrative embodiments of various aspects of the present invention will now be described in detail. Numerous specific details are set forth in the following detailed description to provide a thorough understanding of the invention. However, it will be apparent to those skilled in the art that the invention may be practiced without requiring some of these specific details. The following description of embodiments is merely intended to provide a better understanding of the invention by illustrating examples of the invention. The invention is by no means limited to any specific setups and methods set forth below, but covers any improvements, substitutions, and modifications to structures, methods, and devices without departing from the spirit of the invention. Well-known structures and techniques are not shown in the drawings and the following description to avoid unnecessarily obscuring the invention.

[0110] It should be noted that, unless otherwise specified, the embodiments of the present invention and the features thereof can be combined with each other, and the various embodiments can be referenced and cited in each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0111] An integrity monitoring method for shipboard inertial / radar integrated navigation systems, such as... Figure 1 As shown, it includes the following steps:

[0112] Step 1. Integrity risk classification.

[0113] The total integrity risk is divided into three categories: fault-free integrity risk (hereinafter abbreviated as FF:FaultFree) and integrity risk based on fault detection mode (hereinafter abbreviated as FD:FaultDetected).

[0114] Step 2: Classification of integrity indicators.

[0115] According to system integrity requirements, the total probability of generating misleading hazardous information is defined as PHMI (probability of Misleading Hazardous Information).

[0116] Based on the scenario in step 1, the probability of misleading hazard information is divided into: probability of misleading hazard information without fault (PHMI).FF and Probability of Misleading Fault Detection Information (PHMI) FD The probability of PHMI based on fault detection danger misleading information FD According to the distance measurement, azimuth angle, and elevation angle respectively: Distance Measurement PHMI FD1 Azimuth PHMI FD2 Altitude angle PHMI FD3 .

[0117] Step 3. Establish a filtered state equation model for the ship-oriented inertial / radar integrated navigation system, such as... Figure 2 As shown, the measurement equation model is further set up;

[0118] Step 3.1 The filter state variables of the integrated navigation system are updated as follows:

[0119] The state variables of the inertial navigation system in the Earth coordinate system e are defined as follows:

[0120]

[0121] In the state variables, δP e For the 3D position error in the e-frame, δV e For the 3D velocity error in the e-frame, For 3D attitude misalignment angle error, δb a For 3D accelerometer zero bias, δb g It is a 3D gyroscope with zero bias.

[0122] The system state equations are as follows:

[0123]

[0124] Next, time updates are performed, and the one-step prediction Xk / k-1 and the one-step prediction mean square error matrix Pk / k-1 are calculated according to the following formula:

[0125] X K / K-1 =φ K / K-1 ·X K-1

[0126]

[0127] Among them, Q K-1 Based on the system noise matrix, specific values ​​can be set according to the actual situation.

[0128] Step 3.2 Based on the state update results, perform measurement updates:

[0129] Let L D , λ D h D For the latitude, longitude, and altitude of the radar ranging station, L ψ, λ ψ h ψ For the latitude, longitude, and altitude of the radar azimuth station, L θ , λ θ h θ Provide the latitude, longitude, and altitude of the radar azimuth station;

[0130] ρ D ,ψ D ,θ D Radar measurement parameters: slant range, azimuth, and elevation;

[0131] Convert the latitude, longitude, and altitude of the station to a fixed rectangular coordinate system:

[0132]

[0133] Among them, R N Let be the Earth's radius, and e be the Earth's eccentricity.

[0134] Calculate the corrected inertial navigation position:

[0135] Lat = Lat_ins-X INS_k / k-1 [1]

[0136] Lon = Lon_ins-X INS_k / k-1 [2]

[0137] height = hX NS_k / k-1 [3]

[0138] Where Lat_ins represents the local latitude calculated by inertial coordinates, and Lon_ins represents the local longitude calculated by inertial coordinates. The corrected position is then transformed from the geographic coordinate system to the Earth's fixed rectangular coordinate system:

[0139] x=(R N +height)cos(Lat)cos(Lon)

[0140] y = (R) N +height)cos(Lat)sin(Lon)

[0141] z = [R] N (1-e 2 )+height]sin(Lat)

[0142] Based on the inertial correction position (x, y, z) in the above fixed rectangular coordinate system and the station position (x D ,y D ,z D Further calculations were performed on the intermediate distance measurements:

[0143]

[0144] in,

[0145] Similarly, calculate the intermediate measurement of the azimuth:

[0146]

[0147] in,

[0148] Similarly, calculate the intermediate height measurement:

[0149]

[0150] in,

[0151] Based on the intermediate measurements in the above steps, the equivalent measurement is calculated as follows:

[0152] Calculate the equivalent slope distance based on intermediate measurements during distance measurement:

[0153]

[0154] Calculate the equivalent azimuth angle ψ based on intermediate azimuth measurements. C :

[0155]

[0156] In the above formula, Δλ=Lon-λ ψ ;

[0157] Calculate the equivalent elevation angle based on the intermediate azimuth measurement:

[0158]

[0159] In summary, the calculation equation is as follows:

[0160]

[0161] The measurement transition matrix is ​​calculated as follows:

[0162]

[0163] The B matrix is ​​calculated using the corrected inertial navigation positions Lat, Lon, and height.

[0164]

[0165] Substituting the above calculation results into the first 3×3 dimensions of the Hk matrix (3*number of states), the remaining elements of Hk are 0;

[0166] R kThe parameters of the matrix are determined based on the actual situation;

[0167] Based on this, the covariance P of the measurement update results is calculated. k and state estimation X K :

[0168]

[0169] X K =X K / K-1 +K K ·Z K

[0170] P k =(IK k *H k )*P k / k-1 *(IK k *H k ) T +K k *R k *K k T .

[0171] Among them, K K R is the filter gain coefficient. K This is the measurement noise matrix.

[0172] Step 4. Figure 2 As shown, the integrity index is further decomposed, and the integrity level protection threshold HPL under fault-free conditions is calculated based on the measurement equation model output in step 3. FF ;

[0173] Step 4.1 Calculate the attitude projection matrix from the Earth-centered Earth-fixed coordinate system (ECEF) to the navigation system. Then, the projection of the filter covariance in step 3 onto the N-system is obtained:

[0174]

[0175] in, The calculation method is as follows:

[0176]

[0177] Among them, R N Where is the Earth's radius, e is the Earth's eccentricity, Lat is the local latitude, and Lon is the local longitude;

[0178] The converted inertial / satellite combined filter Pk N Calculate the largest eigenvalue of the covariance matrix:

[0179]

[0180] Step 4.2 Calculate the level of protection under the fault-free integrity risk assumption based on the largest eigenvalue of the covariance matrix:

[0181]

[0182] Among them, K H0 Based on PHMI FF The calculation is based on the Rayleigh distribution's confidence interval, as follows:

[0183] K FF =raylinv(1-PHMI) FF ).

[0184] Step 5. Calculate the integrity level protection threshold (HPL) under fault detection mode based on the measurement equation model output in Step 3. FD ;

[0185] Step 5.1 Calculate the measurement residual: r K =Z K -H k X k / k-1

[0186] Step 5.2 Based on Step 5.1, perform fault detection analysis:

[0187] When there are no faults, r K =Z K -H k X k / k-1 It follows a normal distribution N(0,A) with zero mean K ), where A K The variance of the normal distribution is calculated as follows:

[0188] A K =H K P K (H K ) T +R K

[0189] Step 5.3 For each dimension of the measurement residual r i Construct the detection function λ i =r i T r i Its detection threshold D i for:

[0190] D i =K FA *sqrt(A kii )

[0191] Where KFA Based on the system's false alarm rate index P for radar faults ML The decision is made, and the specific calculation method is as follows:

[0192] K FAi =Q -1 (1-P ml i)

[0193] The above D i Projecting onto the geographic coordinate system, we get D. H .

[0194] Step 5.4 then determines the horizontal detection threshold:

[0195]

[0196] Step 5.5, based on Step 5.4, determines the integrity protection level:

[0197] HPL FD The integrity protection level is calculated by projecting the residual detection threshold onto the geographic coordinate system based on the inertial / radar combined detection capability.

[0198] HPL FD =D H +K Hmd σ H

[0199] Among them, K Hmd =raylinv(1-PHMI) FD i / P Fault i), P Fault i represents the probability that the measurement in this dimension will have a bias due to a fault, i.e., PHMI FD i / P Fault i represents the probability of a missed alarm due to a fault.

[0200] σ H This is the 1σ value of the horizontal error of the inertial / radar combination.

[0201] Step 6. Based on the fault-free integrity level protection threshold HPL obtained in Step 4. FF The integrity level protection threshold (HPL) obtained in step 5 under the fault detection mode FD Integrity protection level for calculated inertial / satellite combined output parameters:

[0202] HPL F =max(HPL) GNSS HPL H0 HPL FD )

[0203] HPL GNSSThe horizontal protection threshold for satellite space signals is transmitted from the outside.

Claims

1. A method for monitoring the integrity of an inertial / radar combination for shipboard landing, characterized in that, Includes the following steps: Step 1: Based on the presence or absence of faults, the total integrity risk is divided into fault-free integrity risk and integrity risk based on fault detection mode; Step 2: Based on the integrity requirements of the inertial / radar integrated navigation system, set the probability of dangerous misleading information under each risk type in Step 1, and denot it as the probability of fault-free dangerous misleading information PHMI. FF and Probability of Misleading Fault Detection Information (PHMI) FD ; Step 3: Establish the filtered state equation model of the ship-landing inertial / radar integrated navigation system, and further set the measurement equation model; In Step 3, the specific process of establishing the filtered state equation model of the ship-landing inertial / radar integrated navigation system includes: defining the state quantities of the inertial navigation system in the Earth coordinate system e as follows: Wherein, δP e For the 3D position error in the e-frame, δV e For the 3D velocity error in the e-frame, For 3D attitude misalignment angle error, δb a For 3D accelerometer zero bias, δb g Zero bias for 3D gyroscope; The filter state equation model for the inertial / radar integrated navigation system is as follows: Next, a time update is performed, and the state is predicted in one step according to the following formula: X. k / k-1 One-step prediction mean square error matrix P k / k-1 : Wherein, the noise parameter matrix Q K-1 Based on the system noise matrix, specific values ​​can be set according to the actual situation; Covariance state transition matrix; Step 4: Based on the measurements output from the measurement equation model in Step 3, and combined with the probability of misleading information under each risk type in Step 2, calculate the integrity level protection threshold (HPL) under fault-free conditions. FF ; Step 4 specifically includes the following steps: Step 4.1 Calculate the attitude projection matrix from the Earth-centered Earth-fixed coordinate system (ECEF) to the navigation system. Then, the projection of the filter covariance in step 3 onto the N-system is obtained: in, The calculation method is as follows: Among them, R N Let be the Earth's radius, e be the Earth's eccentricity, Lat be the local latitude, and Lon be the local longitude; Pk is the converted inertial / radar combined filter. N Calculate the largest eigenvalue of the covariance matrix: Step 4.2 Calculate the level of protection under the fault-free integrity risk assumption based on the largest eigenvalue of the covariance matrix: Among them, K FF Based on PHMI FF The calculation is based on the Rayleigh distribution's confidence interval, as follows: K FF =raylinv(1-PHMI FF ); Step 5: Based on the measurements output from the measurement equation model in Step 3, and combined with the probability of misleading information under each risk type in Step 2, calculate the integrity level protection threshold (HPL) under the fault detection mode. FD ; Step 6: Based on the fault-free integrity level protection threshold HPL obtained in Step 4. FF The integrity level protection threshold (HPL) obtained in step 5 under the fault detection mode FD The integrity protection level of the inertial / satellite combination output parameters is calculated.

2. The inertial / radar combination integrity monitoring method for shipboard landing as described in claim 1, characterized in that, In step 3, the specific process of setting the measurement equation model includes: updating the measurement based on the state update results. Let L D , λ D h D For the latitude, longitude, and altitude of the radar ranging station, L ψ , λ ψ h ψ For the latitude, longitude, and altitude of the radar azimuth station, L θ , λ θ h θ For the radar altitude station's latitude, longitude, and altitude; ρ D ,ψ D ,θ D These are the slant range, azimuth, and elevation parameters measured by the radar, respectively. The latitude, longitude, and altitude of the radar ranging station are converted to the Earth's fixed rectangular coordinate system according to the following formula; Find the coordinates of the radar ranging station in the Earth's fixed rectangular coordinate system: Determine the coordinates of the radar azimuth station in a fixed rectangular coordinate system on Earth: Determine the coordinates of the radar elevation station in a fixed rectangular coordinate system: Among them, R N Let be the Earth's radius, and e be the Earth's eccentricity. Calculate the corrected inertial navigation position: Lat=Lat_ins-X INS_k / k-1 [1] Lon=Lon_ins-X INS_k / k-1 [2] height=h-X INS_k / k-1 [3] Among them, X INS_k / k-1 As a one-step state transition variable, Lat_ins is the local latitude calculated by the inertial system, Lon_ins is the local longitude calculated by the inertial system, and h is the inertial atmospheric damping height; the corrected inertial navigation position is transformed from the geographic coordinate system to the Earth's fixed rectangular coordinate system: x=(R N +height)cos(Lat)cos(Lon) y=(R N +height)cos(Lat)sin(Lon) z=[R N (1-e 2 )+height]sin(Lat) Based on the corrected inertial navigation position (x, y, z) and station position (x, y, z) in the above fixed rectangular coordinate system. D ,y D ,z D The intermediate distance measurement is calculated using the following formula: in, Calculate the intermediate azimuth measurement using the following formula: in, Calculate the intermediate height measurement using the following formula: in, Based on the intermediate measurements in the above steps, the equivalent measurement is calculated as follows: Calculate the equivalent slope distance based on intermediate measurements during distance measurement: Calculate the equivalent azimuth angle ψ based on intermediate azimuth measurements. C : In the above formula, Δλ=Lon-λ ψ ; Calculate the equivalent elevation angle based on the intermediate azimuth measurement: In summary, the calculation equation is as follows: The measurement transition matrix is ​​calculated as follows: The B matrix is ​​calculated using the corrected inertial navigation positions Lat, Lon, and height. Substituting the above calculation results into the first 3×3 dimensions of the Hk matrix, H k All other elements are 0; R k The parameters of the matrix are determined based on the actual situation; Based on this, the covariance P of the measurement update results is calculated. k and state estimation X K : X K =X K / K-1 +K K ·Z K P k =(I-K k *H k )*P k / k-1 *(I-K k *H k ) T +K k *R k *K k T Among them, K K R is the filter gain coefficient. K This is the measurement noise matrix.

3. The inertial / radar combination integrity monitoring method for shipboard landing as described in claim 2, characterized in that, Step 5 specifically includes the following steps: Step 5.1 Calculate the measurement residual: r K =Z K -H k X k / k-1 Step 5.2 Based on Step 5.1, perform fault detection analysis: When there are no faults, r K =Z K -H k X k / k-1 It follows a normal distribution with zero mean N(0,A) K ), where A K The variance of the normal distribution is calculated as follows: A K =H K P K (H K ) T +R K Step 5.3 For each dimension of the measurement residual r i Construct the detection function λ i =r i T r i Its detection threshold D i for: D i =K FA *sqrt(A kii ) Where K FA Based on the system's false alarm rate index P for radar faults ML The decision is made, and the specific calculation method is as follows: K FAi =Q -1 (1-P ml i) The above D i Projecting onto the geographic coordinate system, we get D H ; Step 5.4 then determines the horizontal detection threshold: Step 5.5, based on Step 5.4, determines the integrity protection level: HPL FD Based on the combined inertial / radar detection capability, the detection threshold of residual detection is projected onto the geographic coordinate system to calculate the integrity protection level. HPL FD =D H +K Hmd σ H Among them, K Hmd =raylinv(1-PHMI) FD i) σ H This is the 1σ value of the horizontal error of the inertial / radar combination.

4. A ship-landing-oriented inertial / radar combination integrity monitoring device, used to implement the ship-landing-oriented inertial / radar combination integrity monitoring method according to any one of claims 1-3, characterized in that, include: The system comprises the following components: a filter state equation model construction unit for the inertial / radar integrated navigation system, used to establish a filter state equation model for the ship-landing-oriented inertial / radar integrated navigation system; a measurement equation model construction unit, used to further set up a measurement equation model based on the filter state equation model for the ship-landing-oriented inertial / radar integrated navigation system; and a fault-free integrity level protection threshold calculation unit, used to calculate the fault-free integrity level protection threshold HPL based on the measurements output from the measurement equation model and the probability of misleading information under various risk types. FF The integrity level protection threshold calculation unit in fault detection mode is used to calculate the integrity level protection threshold (HPL) in fault detection mode based on the measurements output from the measurement equation model and the probability of misleading hazard information under each risk type. FD Inertial / satellite integrated inertial navigation system integrity protection level calculation unit, used to calculate the integrity protection level (HPL) of the inertial / satellite integrated inertial navigation system. GNSS .

5. A computer storage medium, characterized in that, The system contains a computer program that, when executed by a processor, implements a ship-oriented inertial / radar combination integrity monitoring method as described in any one of claims 1-3.

6. A computer program product containing instructions, characterized in that, When the computer program product is run on a computer, the computer performs a ship-landing-oriented inertial / radar combination integrity monitoring method as described in any one of claims 1-3.

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