IntroductionADS-B is theabbreviation for broadcast-related automatic surveillance. It mainly implementsair-to-air surveillance. Generally, it only needs on-board electronic devices(GPS receiver, data link transceiver and antenna, Cockpit Conflict InformationDisplay CDTI ) That does not require any ground support equipment and that anADS-B equipped aircraft can broadcast its own precise location and other data(such as speed, altitude and whether the aircraft turns, climbs or descents,etc.

) through the data link. The ADS-B receiver, combined with the ATC systemand other aircraft’s on-board ADS-B, provides accurate and real-time collisioninformation in the open space. ADS-B is a completely new technology thatredefines the three elements of today’s air traffic control communications,navigation and surveillance. Automatic- automatic, “all-weather operation”, without duty.

Dependent- it only needs to rely on accurate global positioning data of the satellitenavigation. Surveillance- Surveillance, surveillance (gain) aircraft position, altitude, speed,heading, identification number and other information. Broadcast- Broadcast, unanswered, airplanes or ground stations broadcasting each other’sown data messages.

ADS-B system consistsof multi-ground stations and airborne stations to form a network, multi-pointto multi-point data to complete the two-way communication. Airborne ADS-Bcommunication equipment broadcasts navigation information collected by airborneinformation processing units, receives broadcast information from otheraircrafts and terrestrials, and processes the same to give a comprehensiveinformation display to the cabin. Based on ADS-B information collected fromother aircraft and ground, airborne radar information and navigationinformation, the integrated information display provides pilots withsituational information and other additional information about the aircraft(eg, collision warning information, collision avoidance strategies, weatherinformation ). ADS-B system is acollection of communications and surveillance in one of the informationsystems, information sources, information transmission channels and informationprocessing and display of three parts.

ADS-B’s main information is theaircraft’s 4-dimensional location information (longitude, latitude, altitudeand time) and other possible additional information (collision warninginformation, pilot input, track angle, inflection point and other information)and aircraft identification information And category information. In addition,it may include some additional information such as heading, airspeed, windspeed, wind direction and temperature outside the aircraft. Disadvantage of ADS-B system1)Related surveillance relies entirely on airborne navigation sources ADS-Bitself does not have the verification function of the information source, theground station equipment (system) cannot be discerned if the positioninformation given by the aircraft is wrong; ADS-B cannot work normally in thecase of GNSS failure; 2)Information processing time is long, communication lags behind Therefore, there isnecessary to find a new system such that ADS-B will not fail in the case ofGNSS failure. In this case, combine two navigation system together is a betterapproach. Strapdown inertialnavigation systems and global navigation satellite systems have their owndistinct advantages and disadvantages, SINS has the advantages of anti-jamming,but there is a fatal flaw in positioning accuracy over time: satellite navigationsystems is with high positioning accuracy, and positioning accuracy does notdiverge with time but weak navigation satellite signals vulnerable tointerference. The combination of these two satellite Inertial Navigation Systemcan overcome the shortcomings of both to play the strengths of both to achievecomplementary advantages. According to the level of information fusion,satellite inertial integrated navigation system can be divided into loosecombination, tight combination, ultra tight combination and deep integratednavigation system.

Among them, the loosely combined and tight integratednavigation system does not improve the loop performance of the satellitereceiver. The ultra-tight integrated navigation and deep integrated navigationuse the inertial information aided tracking loop to improve the performance ofsatellite navigation receiver tracking loop. One of the key technologies ofdeep integrated navigation system based on vector tracking is high performancevector tracking loop. Some domestic and foreign researchers have done a lot ofresearches on deep inertial combination of satellite based on vector trackingloop. Based on Matlab and Sigmaplot Software platform to build avector-tracking software receiver and details of the implementation details andparameter setting details, and based on this platform to build a vectortracking deep combination of guidance air system, and tested it. Wang Xinlonget al at Beijing University of Aeronautics and Astronautics researched a SINS /GPS integrated deep navigation method based on vector tracking. The simulationproves the excellent performance of the vector tracking deep integratednavigation system, which can guarantee the performance of the integratednavigation system Navigation accuracy and reliability.

Draper Laboratory,Aerospace Corporation and Raython Corporation, MIT overseas institutes putforward their own deep integrated navigation system, which proves that thevector tracking deep integrated navigation system has stronger anti-jammingperformance. At present, the research of vector tracking deep integratednavigation system mainly focuses on reducing the amount of computation andimproving system fault tolerance. At present, there are few researches onfault-tolerant of deep tracking navigation system based on vector tracking.

Inthis paper, we propose a new channel subfilter and state detection function todetect the possible influence of abnormal channel on normal channel in deepnaval navigation status. Inthis paper, the basic principle of vector tracking deep integrated navigationsystem is firstly analyzed. Aiming at the problem of channel status detectionof deep integrated navigation system under the condition of frequent occlusionof some satellite signals, a subfilter and its corresponding subfilter statedetection function are designed.

Used to detect the channel running status, andfinally verify and analyze the performance of the algorithm through simulationexperiments. 1 Fault-tolerant deep integratednavigation system1.1 Deep combination navigationsystemFigure1 is a fault-tolerant vector tracking deep composite navigation systemstructure, fault-tolerant deep integrated navigation system is mainly composedof vector receiver module, inertial navigation module and integrated navigationmodule. This program retains the vector tracking receiver navigation filter,mainly for two reasons, the first point, so you can reduce the operatingfrequency of the combined navigation filter, the navigation signal is not usedin the calculation of navigation information Tracking loop parameters to updatethe vector tracking loop; the second point, this design for the entireintegrated navigation system in terms of retaining the entire vector receiversystem for measuring the channel state of operation, the sub-filter model andfault detection function in detail 1.2 and 1.3 1.2 sub-filter modelStateequation of sub-filter model: ??k+1 0 T ??k v? ??’k+1 = T 0 · ??’k + v?’ In the formula, ??k+1, ??’k+1 are K +1 moment pseudorange,pseudo-range error, T is the filter period of 1ms, ??k, ??’k are k moment pseudorange, pseudo-rangeerror, v?, v?’ are pseudo-range, pseudo-range systemnoise, respectively.

Sub-filter model of the measurement equation:zncode 1 0 ??k ?? zncarrier = 0 1 · ??’k + ??’ In the formula, zncode, zncarrier are for the channel n pseudo-range,pseudo-range measurement, respectively; ??k, ??’k are k moment pseudorange, pseudo-rangeerror, respectively; ??, ??’ are pseudo-range, pseudo-range system noise,respectively. 1.3 state detection functionNavigation filter forthe Kalman filter is calculated as follows:Consider a lineardiscrete system: xk = ?k,k-1 xk-1 + wk-1 zk =HK xk + vk among them, xk is defined to be the moment k statevector, ?k,k-1 is defined to be the state transition matrix, zk is defined to be the measurement vector, HK isdefined to be the measurement matrix, and wk-1, vkare defined to be the system and measurement noise, and satisfy thefollowing: E{wk} = 0, E{ wk wTj}= Qk E{vk} = 0, E{ vk vTj}= Rk E{ vk wTj} =0 In the above equations, Qk >= 0 is the system noise variance matrix; Rk > 0 is themeasuring noise variance matrix.x’k,k-1 =?k,k-1 x’k-1x’k = x’k,k-1 + Kk(zk- HK x’k,k-1)Kk = Pk,k-1 HTk(HKPk,k-1 HTk + Rk)-1Pk,k-1 =?k,k-1 Pk-1 ?Tk,k-1 + Qk-1Pk = (1 – Kk HK) Pk,k-1 among them, x’k,k-1 is the state prediction, Kk is the filter gain matrix, Pkis the covariance matrix. Residual is defined to be:rk = zk – HK x’k,k-1 It can be proved that the residual rk iszero-mean Gaussian white noise when the filter is fault-free, the variance is:Ak = HK Pk,k-1 HTk+ RkWhen the system fails, the mean value of theresidual rk will not be zero, the fault detection function is asfollows:?k = rTk A-1krkIn the above formula, ?k is in chi-squared distribution with degree freedom of m, where m is themeasurement dimension of zk. Judgment criteria are as follows: ?2m (k) > TD, it is abnormal ?2m (k) < TD, it is in the normal working condition When the channel is judged to be abnormal, theresponse method is as follows:1) According to equation Kk = Pk,k-1HTk(HK Pk,k-1 HTk +Rk)-1 , if Rk is a diagonal matrix and the jthelement is set to a large value, then R-1k(:, j) -> 0, so Kk(:, j) -> 0 .2) According to equation x’k = x’k,k-1 + Kk(zk – HK x’k,k-1), we can see the j-th component of zk measure contributeslittle or nothing to the state estimate effect x’k. 1.

4combined navigation filterIn the integrated navigation system, the Kalmanfilter used by both the vector receiver and the combined navigation filter, andthe system state variables of the Kalman filter in the integrated navigationsystem take the error quantities of the navigation output parameters, includingSINS output error and GNSS receiver output error . The system’s state variablesare:X = XI XGT among them, XI is SINS error variable,the concrete form is:XI = ?E ?N ?U ?VE ?VN ?VU ?L ?? ?h ?x ?y ?z ?x ?y ?z In the above formula, ?E ?N ?U are theattitude error angle in east, north and upward direction; ?VE ?VN ?VU are the velocity error in the east, north and sky direction; ?L ?? ?h are the latitude, longitude and height error; ?x ?y ?z are the random drift of thethree gyroscopes in the carrier system; ?x ?y ?z are thecommon bias of the accelerometer in the three axial directions of the carriersystem, XG is GNSS error variables ofclock driftXG = ?tu ?tru T System Measurement Inputs Pseudo-range andPseudo-range Estimation for Sub-Filter is:Z = zp = Hp X + Vp = HX + V zp’ Hp’ Vp’ 2Simulation and Result Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 ConclusionAiming at the robustness of vector trackingdeep integrated navigation system, a GNSS / SINS fault tolerant deep integratednavigation system is proposed. First, a simple subfilter is designed for eachchannel, and the state of the subfilter is detected by the detection functionJudging the operation of the channel, when the channel satellite signal isbriefly blocked, it can be timely judged and isolated, thus avoiding theinfluence of the blocked channel on the navigation and positioning accuracy ofthe deep integrated navigation, thereby improving the stability of the system.When the signal appear again, due to the mutual assistance between the vectortracking channels, when the signal reappears, it can immediately be tracked againand incorporated into the navigation filter, thus avoiding the traditionalfault diagnosis method of removing the satellite directly, and when satellitesignals can take full advantage when they reappear all satellite signals.