Introduction information and navigation information, the integrated

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ADS-B is the
abbreviation for broadcast-related automatic surveillance. It mainly implements
air-to-air surveillance. Generally, it only needs on-board electronic devices
(GPS receiver, data link transceiver and antenna, Cockpit Conflict Information
Display CDTI ) That does not require any ground support equipment and that an
ADS-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 system
and other aircraft’s on-board ADS-B, provides accurate and real-time collision
information in the open space. ADS-B is a completely new technology that
redefines the three elements of today’s air traffic control communications,
navigation and surveillance.


– automatic, “all-weather operation”, without duty.

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– it only needs to rely on accurate global positioning data of the satellite


– Surveillance, surveillance (gain) aircraft position, altitude, speed,
heading, identification number and other information.


– Broadcast, unanswered, airplanes or ground stations broadcasting each other’s
own data messages.


ADS-B system consists
of multi-ground stations and airborne stations to form a network, multi-point
to multi-point data to complete the two-way communication. Airborne ADS-B
communication equipment broadcasts navigation information collected by airborne
information processing units, receives broadcast information from other
aircrafts and terrestrials, and processes the same to give a comprehensive
information display to the cabin. Based on ADS-B information collected from
other aircraft and ground, airborne radar information and navigation
information, the integrated information display provides pilots with
situational information and other additional information about the aircraft
(eg, collision warning information, collision avoidance strategies, weather
information ).


ADS-B system is a
collection of communications and surveillance in one of the information
systems, information sources, information transmission channels and information
processing and display of three parts. ADS-B’s main information is the
aircraft’s 4-dimensional location information (longitude, latitude, altitude
and time) and other possible additional information (collision warning
information, 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, wind
speed, wind direction and temperature outside the aircraft.


Disadvantage of ADS-B system

Related surveillance relies entirely on airborne navigation sources


itself does not have the verification function of the information source, the
ground station equipment (system) cannot be discerned if the position
information given by the aircraft is wrong; ADS-B cannot work normally in the
case of GNSS failure;


Information processing time is long, communication lags behind


Therefore, there is
necessary to find a new system such that ADS-B will not fail in the case of
GNSS failure. In this case, combine two navigation system together is a better



Strapdown inertial
navigation systems and global navigation satellite systems have their own
distinct advantages and disadvantages, SINS has the advantages of anti-jamming,
but there is a fatal flaw in positioning accuracy over time: satellite navigation
systems is with high positioning accuracy, and positioning accuracy does not
diverge with time but weak navigation satellite signals vulnerable to
interference. The combination of these two satellite Inertial Navigation System
can overcome the shortcomings of both to play the strengths of both to achieve
complementary advantages. According to the level of information fusion,
satellite inertial integrated navigation system can be divided into loose
combination, tight combination, ultra tight combination and deep integrated
navigation system. Among them, the loosely combined and tight integrated
navigation system does not improve the loop performance of the satellite
receiver. The ultra-tight integrated navigation and deep integrated navigation
use the inertial information aided tracking loop to improve the performance of
satellite navigation receiver tracking loop. One of the key technologies of
deep integrated navigation system based on vector tracking is high performance
vector tracking loop. Some domestic and foreign researchers have done a lot of
researches on deep inertial combination of satellite based on vector tracking
loop. Based on Matlab and Sigmaplot Software platform to build a
vector-tracking software receiver and details of the implementation details and
parameter setting details, and based on this platform to build a vector
tracking deep combination of guidance air system, and tested it. Wang Xinlong
et al at Beijing University of Aeronautics and Astronautics researched a SINS /
GPS integrated deep navigation method based on vector tracking. The simulation
proves the excellent performance of the vector tracking deep integrated
navigation system, which can guarantee the performance of the integrated
navigation system Navigation accuracy and reliability. Draper Laboratory,
Aerospace Corporation and Raython Corporation, MIT overseas institutes put
forward their own deep integrated navigation system, which proves that the
vector tracking deep integrated navigation system has stronger anti-jamming
performance. At present, the research of vector tracking deep integrated
navigation system mainly focuses on reducing the amount of computation and
improving system fault tolerance. At present, there are few researches on
fault-tolerant of deep tracking navigation system based on vector tracking. In
this paper, we propose a new channel subfilter and state detection function to
detect the possible influence of abnormal channel on normal channel in deep
naval navigation status.


this paper, the basic principle of vector tracking deep integrated navigation
system is firstly analyzed. Aiming at the problem of channel status detection
of deep integrated navigation system under the condition of frequent occlusion
of some satellite signals, a subfilter and its corresponding subfilter state
detection function are designed. Used to detect the channel running status, and
finally verify and analyze the performance of the algorithm through simulation



1 Fault-tolerant deep integrated
navigation system

1.1 Deep combination navigation

1 is a fault-tolerant vector tracking deep composite navigation system
structure, fault-tolerant deep integrated navigation system is mainly composed
of vector receiver module, inertial navigation module and integrated navigation
module. This program retains the vector tracking receiver navigation filter,
mainly for two reasons, the first point, so you can reduce the operating
frequency of the combined navigation filter, the navigation signal is not used
in the calculation of navigation information Tracking loop parameters to update
the vector tracking loop; the second point, this design for the entire
integrated navigation system in terms of retaining the entire vector receiver
system for measuring the channel state of operation, the sub-filter model and
fault detection function in detail 1.2 and 1.3




1.2 sub-filter model

equation of sub-filter model:

 ??k+1               0  T       ??k       v?

  ??’k+1       =  
T  0    ·  
+   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-range
error, v?, v?’ are pseudo-range, pseudo-range system
noise, 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-range
error, respectively; ??, ??’ are pseudo-range, pseudo-range system noise,



1.3 state detection function

Navigation filter for
the Kalman filter is calculated as follows:

Consider a linear
discrete system:

   xk = ?k,k-1 xk-1 + wk-1

   zk =
HK xk + vk


among them, xk is defined to be the moment k state
vector, ?k,k-1 is defined to be the state transition matrix, zk is defined to be the measurement vector, HK is
defined to be the measurement matrix, and wk-1, vk
are defined to be the system and measurement noise, and satisfy the

   E{wk} = 0, E{ wk wTj}
= Qk

   E{vk} = 0, E{ vk vTj}
= Rk

   E{ vk wTj} =



In the above equations, Qk >= 0  is the system noise variance matrix;  Rk > 0       is the
measuring noise variance matrix.

x’k,k-1  =?k,k-1 x’k-1

x’k = x’k,k-1 + Kk(zk
– HK x’k,k-1)

Kk = Pk,k-1 HTk(HK
Pk,k-1 HTk + Rk)-1

Pk,k-1 =?k,k-1 Pk-1 ?Tk,k-1 + Qk-1

Pk = (1 – Kk HK) Pk,k-1


among them, x’k,k-1 is the state prediction, Kk is the filter gain matrix, Pk
is the covariance matrix.


Residual is defined to be:

rk = zk – HK x’k,k-1


It can be proved that the residual rk is
zero-mean Gaussian white noise when the filter is fault-free, the variance is:

Ak = HK Pk,k-1 HTk
+ Rk

When the system fails, the mean value of the
residual rk will not be zero, the fault detection function is as

?k = rTk A-1k

In the above formula, ?k is in chi-squared distribution with degree freedom of m, where m is the
measurement 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, the response method is as follows: 1) According to equation Kk = Pk,k-1 HTk(HK Pk,k-1 HTk + Rk)-1 , if Rk is a diagonal matrix and the jth element 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 contributes
little or nothing to the state estimate effect x’k.  



combined navigation filter

In the integrated navigation system, the Kalman
filter used by both the vector receiver and the combined navigation filter, and
the system state variables of the Kalman filter in the integrated navigation
system take the error quantities of the navigation output parameters, including
SINS output error and GNSS receiver output error . The system’s state variables



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 the
attitude 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 the
three gyroscopes in the carrier system; ?x  ?y  ?z       are the
common bias of the accelerometer in the three axial directions of the carrier

       XG is GNSS error variables of
clock drift

XG = ?tu  ?tru T


System Measurement Inputs Pseudo-range and
Pseudo-range Estimation for Sub-Filter is:

Z =   zp     =   Hp   X +  
Vp    = HX + V




Simulation and Result


Figure 1







Figure 2




Figure 3


Figure 4



Figure 5




Aiming at the robustness of vector tracking
deep integrated navigation system, a GNSS / SINS fault tolerant deep integrated
navigation system is proposed. First, a simple subfilter is designed for each
channel, and the state of the subfilter is detected by the detection function
Judging the operation of the channel, when the channel satellite signal is
briefly blocked, it can be timely judged and isolated, thus avoiding the
influence of the blocked channel on the navigation and positioning accuracy of
the deep integrated navigation, thereby improving the stability of the system.
When the signal appear again, due to the mutual assistance between the vector
tracking channels, when the signal reappears, it can immediately be tracked again
and incorporated into the navigation filter, thus avoiding the traditional
fault diagnosis method of removing the satellite directly, and when satellite
signals can take full advantage when they reappear all satellite signals.


Categories: Communications


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