CN103869383B - Based on air data computer and its implementation of Kalman filtering algorithm - Google Patents
Based on air data computer and its implementation of Kalman filtering algorithm Download PDFInfo
- Publication number
- CN103869383B CN103869383B CN201410105051.0A CN201410105051A CN103869383B CN 103869383 B CN103869383 B CN 103869383B CN 201410105051 A CN201410105051 A CN 201410105051A CN 103869383 B CN103869383 B CN 103869383B
- Authority
- CN
- China
- Prior art keywords
- data
- digital signal
- signal processing
- processing module
- sequence control
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Landscapes
- Measuring Fluid Pressure (AREA)
Abstract
Based on air data computer and its implementation of Kalman filtering algorithm, computing machine comprises sensor assembly, time-sequence control module and digital signal processing module, and sensor assembly comprises digital pressure sensor and analog temperature sensor; Time-sequence control module, by Control timing sequence signal, communicates with digital signal processing module; Digital signal processing module is connected by address bus and data bus with time-sequence control module, completes the transmission of data.The inventive method comprises: initialization; Send look-at-me; Judge whether to receive look-at-me; Receive data; Judge temperature data whether over range; Data prediction; Calculate atmosphere data; Kalman filtering; Send data and failure code; Judge whether to receive data and failure code.The present invention has that precision is high, error is little, good stability and be suitable for the advantage that barometer altitude undergos mutation, and can be used as airborne equipment and is placed on aircraft.
Description
Technical field
The invention belongs to field of computer technology, further relate to a kind of air data computer based on Kalman filtering algorithm in avionics field and its implementation.The present invention can utilize a small amount of initial parameter of the static pressure data, total head data, temperature data etc. of sensor measurement, for aircraft cockpit provides a large amount of parameter relevant with atmosphere data, and direct drivers operating aircraft.
Background technology
In avionics field, the relevant informations such as the height that air data computer calculates, air speed are the key parameters needed for aircraft display system, are therefore widely used.It is low that the air data computer of domestic current use has precision, and error is large, the shortcomings such as data processing time is longer.
The patented claim " a kind of air data computer and its implementation " (patented claim CN201110268698.1 publication number CN102360088B) that Shaanxi Changling Electronic Technology Co., Ltd. proposes discloses a kind of air data computer and its implementation.Computing machine specific implementation step disclosed in this patented claim is, first, this air data computer is made up of baroceptor assembly and digital signal processing assembly; Secondly, the simulating signal that static pressure transducer, total head sensor and temperature sensor export, after amplification, gating and A/D conversion, is sent into first microprocessor and is processed; Then, the static pressure data obtained after process, dynamic pressure data and temperature data, then received by gating signal timesharing by the second microprocessor; Finally, the second microprocessor calculates data and processes, and result is exported by RS422 interface serial.The deficiency that computing machine disclosed in this patented claim exists is that the analog pressure sensor precision selected is lower, poor stability, makes subsequent calculations produce comparatively big error.
The concrete steps of the implementation method disclosed in this patented claim are, first, the second microprocessor calculates data and processes, and obtains barometer altitude, true air speed and indicator air speed and stores; Secondly, after repeating n time, stored a n barometer altitude, true air speed and indicator air speed are averaged; Then, by the mean value computation relative height of barometer altitude; Finally, by comparing the aerodrome elevation that GPS records and the barometer altitude average calculated, revising relative height, obtaining the barometer altitude revised with the relative height by revising.The deficiency that implementation method disclosed in this patented claim exists is, only adopts one group of temperature sensor coefficient, cannot the change of environmentally temperature revise; Cannot revise when catastrophe appears in barometer altitude etc.
Summary of the invention
The present invention is directed to the deficiency that above-mentioned prior art exists, propose a kind of air data computer based on Kalman filtering algorithm and its implementation.The present invention can reduce the error of calculation effectively, improves stability, and the change of environmentally temperature can select corresponding temperature sensor coefficient, can realize quick tracking, and have very strong antijamming capability when aircraft barometer altitude suddenly change.
Computing machine of the present invention, comprises sensor assembly, time-sequence control module and digital signal processing module:
Described sensor assembly comprises digital pressure sensor and analog temperature sensor, and described digital pressure sensor is connected with time-sequence control module respectively with analog temperature sensor; Digital pressure sensor inside is containing two analog to digital converters, under the control of time-sequence control module, two analog to digital converters export static pressure digital signal and total head digital signal respectively, static pressure digital signal and total head digital signal are through amplification, gating, after sending into time-sequence control module process, obtain static pressure data and total head data; The temperature analog signal that described analog temperature sensor exports, after amplification, gating and A/D conversion, is sent into time-sequence control module process, is obtained temperature data;
Described time-sequence control module, by Control timing sequence signal, completes the communication with digital signal processing module; Time-sequence control module sends a look-at-me every 50ms to digital signal processing module; Static pressure data, total head data and airport static pressure data that time-sequence control module reception digital pressure sensor exports and the temperature data that analog temperature sensor exports, by address bus and data bus successively by static pressure data, total head data, airport static pressure data and temperature data, send to digital signal processing module, and judge whether the atmosphere data and the failure code that receive digital signal processing module transmission;
Described digital signal processing module is connected by address bus and data bus with time-sequence control module, completes the transmission between data; Digital signal processing module, to the parameter in analog temperature sensor coefficient, Kalman filtering algorithm, receive data address and need the atmosphere data being sent to time-sequence control module to carry out initialization; Digital signal processing module judges whether the look-at-me receiving time-sequence control module transmission, if the look-at-me of receiving, then after digital signal processing module response look-at-me, received the static pressure data, total head data, temperature data and the airport static pressure data that are sent by time-sequence control module by address bus and data bus; Digital signal processing module judges whether the temperature data received exceeds-40 DEG C ~ 70 DEG C ambient temperature ranges set by analog temperature sensor; After digital signal processing module carries out data prediction to the temperature data received, static pressure data and total head data, calculate atmosphere data; Digital signal processing module adopts the Kalman filtering algorithm of constant accelerator model to upgrade barometer altitude, rising or falling speed, rising or falling speed rate of change; Atmosphere data and failure code, by address bus and data bus, are sent to time-sequence control module by digital signal processing module.
The method concrete steps that the present invention realizes are as follows:
(1) initialization:
Digital signal processing module, to the parameter in analog temperature sensor coefficient, Kalman filtering algorithm, receive data address and need the atmosphere data being sent to time-sequence control module to carry out initialization.
(2) look-at-me is sent:
Time-sequence control module, by timing control signal, sends a look-at-me every 50ms to digital signal processing module.
(3) judge whether to receive look-at-me:
Digital signal processing module judges whether the look-at-me receiving time-sequence control module transmission, if the look-at-me of receiving, then after digital signal processing module response look-at-me, received the data of time-sequence control module transmission by address bus and data bus, perform step (4); If do not receive look-at-me, then return and perform step (2).
(4) data are sent:
Static pressure data, total head data and airport static pressure data that time-sequence control module reception digital pressure sensor exports and the temperature data that analog temperature sensor exports, by address bus and data bus successively by static pressure data, total head data, temperature data and airport static pressure data, send to digital signal processing module.
(5) data are received:
Digital signal processing module receives the static pressure data, total head data, temperature data and the airport static pressure data that are sent by time-sequence control module.
(6) temperature data whether over range is judged:
Digital signal processing module judges whether the temperature data received exceeds-40 DEG C ~ 70 DEG C ambient temperature ranges set by analog temperature sensor, if exceeded, performs step (10); Otherwise, perform step (7).
(7) data prediction:
(7a) digital signal processing module is to the temperature data received, and removes maximal value wherein and minimum value respectively, and residuals temperatures data are got average, obtains pretreated temperature data;
(7b) digital signal processing module gets average to the static pressure data received and total head data respectively, obtains pretreated static pressure data and total head data.
(8) atmosphere data is calculated:
(8a) according to the following formula, calculating needs the total Air Temperature being sent to time-sequence control module:
T
T＝kT
p+b
Wherein, T
trepresent and need the total Air Temperature being sent to time-sequence control module, T
prepresent pretreated temperature data, k, b represent as the straight slope corresponding to the correction factor of analog temperature sensor and intercept respectively;
(8b) digital signal processing module, to the static pressure data after data prediction and total head data, according to the computing formula provided in selected digital pressure sensor handbook, obtains and needs the air static pressure and the air total head that are sent to time-sequence control module;
(8c) digital signal processing module, the total Air Temperature of time-sequence control module, air static pressure, air total head and airport static pressure data will be needed to be sent to, as known atmosphere data parameter, the pressure-height formula of adopting international standards under air, obtains barometer altitude, relative barometric pressure height, rising or falling speed, rising or falling speed rate of change, indicator air speed, indicator air speed rate of change, true air speed, Mach number, large Pneumatic pressure, Static Air Temperature.
(9) Kalman filtering:
Digital signal processing module, to barometer altitude, rising or falling speed, rising or falling speed rate of change, adopts the Kalman filtering algorithm of constant accelerator model, obtains the barometer altitude, rising or falling speed and the rising or falling speed rate of change that upgrade.
(10) data and failure code is sent:
Atmosphere data and failure code, by address bus and data bus, are sent to time-sequence control module by digital signal processing module.
(11) judge whether to receive data and failure code:
Time-sequence control module judges whether the atmosphere data and the failure code that receive digital signal processing module transmission, if the data of receiving and failure code, then time-sequence control module sends to digital signal processing module answer signal, returns and performs step (2); Otherwise, return and perform step (10).
The present invention compared with prior art has the following advantages:
First, because computing machine of the present invention has selected high-precision digital pressure sensor at sensor assembly, overcome prior art and select low precision analog pressure transducer, poor stability, make subsequent calculations generation compared with the shortcoming of big error, the present invention is had, and precision is high, the advantage of good stability.
Second, due to method of the present invention use least square method to obtain-40 DEG C ~ 70 DEG C environment temperatures under corresponding 23 groups of temperature sensor correction factors, overcome prior art and only adopt one group of temperature sensor coefficient, the change of environmentally temperature cannot carry out the shortcoming revised, make the present invention have gradually subenvironment temperature and, on the impact of temperature sensor, obtain the advantage of equilibrium temperature data.
3rd, because method of the present invention adopts Kalman filtering algorithm to barometer altitude, rising or falling speed, rising or falling speed rate of change, overcome the shortcoming cannot revised when prior art occurs catastrophe to barometer altitude, the present invention is had and can realize when aircraft barometer altitude flip-flop following the tracks of fast, and have very strong antijamming capability, the advantage of good stability.
Accompanying drawing explanation
Fig. 1 is the structured flowchart of computing machine of the present invention;
Fig. 2 is the process flow diagram of implementation method of the present invention.
Embodiment
Below in conjunction with accompanying drawing, the present invention is described in further detail.
With reference to accompanying drawing 1, computing machine of the present invention comprises sensor assembly, time-sequence control module and digital signal processing module.
Sensor assembly is made up of digital pressure sensor and analog temperature sensor, and digital pressure sensor is connected with time-sequence control module respectively with analog temperature sensor.In embodiments of the invention, digital pressure sensor selects IPT0020A33R-E10-20PSI type high accuracy number pressure transducer, digital pressure sensor inside is containing two analog to digital converters, under the control of time-sequence control module, two analog to digital converters export static pressure digital signal and total head digital signal respectively, static pressure digital signal and total head digital signal are through amplifying, gating, after sending into time-sequence control module process, obtain static pressure data and total head data, the simulating signal that described analog temperature sensor exports is through amplifying, after gating and A/D change, send into time-sequence control module process, obtain temperature data,
In embodiments of the invention, time-sequence control module selects EP2C35F484I8 type field programmable logic device (FieldProgrammableGateArray, FPGA), by Control timing sequence signal, completes the communication with digital signal processing module; Time-sequence control module sends a look-at-me every 50ms to digital signal processing module; Static pressure data, total head data and airport static pressure data that time-sequence control module reception digital pressure sensor exports and the temperature data that analog temperature sensor exports, by address bus and data bus successively by static pressure data, total head data, airport static pressure data and temperature data, send to digital signal processing module, and judge whether the atmosphere data and the failure code that receive digital signal processing module transmission;
In embodiments of the invention, digital signal processing module selects TMS320VC5410A type digital signal processor (DigitalSignalProcessing, DSP), be connected by address bus and data bus with time-sequence control module, complete the transmission between data; Digital signal processing module, to the parameter in analog temperature sensor coefficient, Kalman filtering algorithm, receive data address and need the atmosphere data being sent to time-sequence control module to carry out initialization; Digital signal processing module judges whether the look-at-me receiving time-sequence control module transmission, if the look-at-me of receiving, then after digital signal processing module response look-at-me, received the static pressure data, total head data, temperature data and the airport static pressure data that are sent by time-sequence control module by address bus and data bus; Digital signal processing module judges whether the temperature data received exceeds-40 DEG C ~ 70 DEG C ambient temperature ranges set by analog temperature sensor; After digital signal processing module carries out data prediction to the temperature data received, static pressure data and total head data, calculate atmosphere data; Digital signal processing module adopts the Kalman filtering algorithm of constant accelerator model to upgrade barometer altitude, rising or falling speed, rising or falling speed rate of change; Atmosphere data and failure code, by address bus and data bus, are sent to time-sequence control module by digital signal processing module.
With reference to accompanying drawing 2, the concrete steps of the inventive method are described in detail as follows:
Step 1, initialization.
Digital signal processing module, to the parameter in analog temperature sensor coefficient, Kalman filtering algorithm, receive data address and need the atmosphere data being sent to time-sequence control module to carry out initialization.Digital signal processing module is set to zero by needing the atmosphere data value being sent to time-sequence control module.Under analog temperature sensor being placed in-40 DEG C ~ 70 DEG C environment temperatures, input value and the output valve of one group of analog temperature sensor is recorded every 5 DEG C, record 23 groups of temperature datas altogether, least square method is utilized to simulate straight line to 23 groups of temperature datas respectively, using the slope of straight line and intercept as the correction factor of analog temperature sensor, analog temperature sensor coefficient is set to the correction factor of analog temperature sensor.Digital signal processing module is received the address that the address of data and time-sequence control module send data, be set to same address.Adopt Kalman's constant accelerator model, by the optimum configurations in Kalman filtering algorithm be:
Wherein, Δ t represents that time-sequence control module sends the time interval of twice interruption, F represents the state-transition matrix of aircraft within the interval of delta t time, G represents the noise transition matrix of rising or falling speed rate of change, and H represents barometer altitude observing matrix, and Q represents stochastic process noise covariance matrix, R represents random observation noise covariance matrix, P represents the error co-variance matrix of barometer altitude predicted value, and X represents the state vector of aircraft, and Z represents that aircraft measures vector.
Step 2, sends look-at-me.
Time-sequence control module, by timing control signal, sends a look-at-me every 50ms to digital signal processing module.
Step 3, judges whether to receive look-at-me.
Digital signal processing module judges whether the look-at-me receiving time-sequence control module transmission, if the look-at-me of receiving, then after digital signal processing module response look-at-me, received the data of time-sequence control module transmission by address bus and data bus, perform step 4; If do not receive look-at-me, then return and perform step 2.
Step 4, sends data.
Static pressure data, total head data and airport static pressure data that time-sequence control module reception digital pressure sensor exports and the temperature data that analog temperature sensor exports, by address bus and data bus successively by static pressure data, total head data, temperature data and airport static pressure data, send to digital signal processing module.
Step 5, receives data.
Digital signal processing module receives the static pressure data, total head data, temperature data and the airport static pressure data that are sent by time-sequence control module.
Step 6, judges temperature data whether over range.
Digital signal processing module judges whether the temperature data received exceeds-40 DEG C ~ 70 DEG C ambient temperature ranges set by analog temperature sensor, if exceeded, performs step 10; Otherwise, perform step 7.
Step 7, data prediction.
Digital signal processing module, to the temperature data received, removes maximal value wherein and minimum value respectively, and residuals temperatures data are got average, obtains pretreated temperature data.And respectively average is got to the static pressure data received and total head data, obtain pretreated static pressure data and total head data.
Step 8, calculates atmosphere data.
According to the following formula, calculate and need the total Air Temperature being sent to time-sequence control module,
T
T＝kT
p+b
Wherein, T
trepresent that in the aircraft flight needing to be sent to time-sequence control module, air is compressed the atmospheric temperature at rear stagnation point place, T
prepresent pretreated temperature data, k, b represent respectively as the straight slope corresponding to the correction factor of temperature sensor and intercept.
Digital signal processing module, to the static pressure data after data prediction and total head data, according to the computing formula provided in selected digital pressure sensor handbook, obtain air static pressure and air total head, wherein, air static pressure refers to that aircraft flight face overdraught is not by the atmospheric pressure of disturbance place, and air total head refers to that aircraft is on the aircraft surfaces just to air motion direction, when air-flow is obstructed completely, the pressure recorded.
Air static pressure and air total head are set to P respectively
t, P
s, airport static pressure is set to P
airport, the pressure-height formula under air of adopting international standards, calculates barometer altitude, relative barometric pressure height, rising or falling speed, rising or falling speed rate of change, large Pneumatic pressure, true air speed, indicator air speed, indicator air speed rate of change, Mach number, Static Air Temperature respectively.
Wherein, barometer altitude refers to the height of aircraft apart from standard pressure plane, and standard pressure plane refers to the mean sea level that standard state is 760 mm Hg, temperature is 288.15 Kelvins, density is 1.225 kilograms per cubic meter; It is reference plane that relative height refers to the airport ground level before taking off, the height that the center of gravity of airplane represents relative to this reference field and with gravity potential height; Rising or falling speed refers to the barometer altitude of aircraft increase p.s.; Rising or falling speed rate of change refers to the rising or falling speed of aircraft increase p.s.; Large Pneumatic pressure refers to that desirable incompressible gas acts on the power in unit area when arriving stationary point, is the difference of air total head and air static pressure; True air speed refers to the speed of the relative windstream of aircraft, is the true velocity of aircraft relative to air movement; Indicator air speed refers to the value of true air speed naturalization to standard pressure plane; Indicator air speed rate of change refers to the indicator air speed of aircraft increase p.s.; Mach number refers to the ratio of true air speed and place level air middle pitch velocity of wave propagation; Static Air Temperature refers to atmospheric temperature undisturbed in aircraft flight around.
The computing formula of barometer altitude is as follows:
Wherein, H represents barometer altitude, and unit is rice, P
srepresent air static pressure, unit is kPa.With airport static pressure P
airportreplace the air static pressure P in above formula
s, airport barometer altitude H can be obtained
airport, unit is rice.
The computing formula of relative barometric pressure height is as follows:
H
relatively=H-H
airport
Wherein, H
relativelyrepresent relative barometric pressure height, unit is rice, and H represents barometer altitude, and unit is rice, H
airportrepresent airport barometer altitude, unit is kPa.
The computing formula of rising or falling speed is as follows:
Wherein, V
hn () represents the rising or falling speed in n moment, unit is metre per second (m/s).H (n), H (n-1) represent the barometer altitude in n moment, n-1 moment respectively, and unit is rice.T (n), t (n-1) represent the time in n moment, n-1 moment respectively, and unit is second.
The computing formula of rising or falling speed rate of change is as follows:
Wherein, Δ V
hn () represents the rising or falling speed rate of change in n moment, unit is every square, rice second, V
h(n), V
h(n-1) represent the rising or falling speed in n moment, n-1 moment respectively, unit is metre per second (m/s), and t (n), t (n-1) represent the time in n moment, n-1 moment respectively, and unit is second.
The computing formula of large Pneumatic pressure is as follows:
P
q＝P
T-P
S
Wherein, P
qrepresent large Pneumatic pressure, P
trepresent air total head, P
srepresent air static pressure, unit is kPa.
The computing formula of true air speed is as follows:
Wherein, V represents vacuum tightness, and unit is kilometer per hour, P
qrepresent large Pneumatic pressure, unit is kPa, and H represents barometer altitude, and unit is rice.
Indicator air speed V
icomputing formula as follows:
Wherein, V
irepresent indicator air speed, unit is kilometer per hour, P
qrepresent large Pneumatic pressure, unit is kPa;
The computing formula of indicator air speed rate of change is as follows:
Wherein, Δ V
in () represents the indicator air speed rate of change in n moment, unit is km every square hour, V
i(n), V
i(n-1) represent the indicator air speed in n moment, n-1 moment respectively, unit is kilometer per hour, and t (n), t (n-1) represent the time in n moment, n-1 moment respectively, and unit is second.
The computing formula of Mach number is as follows:
M＝{5[(P
T/P
S)
1/3.5-1]}
1/2
Wherein, M represents Mach number, P
trepresent air total head, unit is kPa, P
srepresent air static pressure, unit is kPa.
The computing formula of Static Air Temperature is as follows:
T
s＝T
T/(1+0.2M
2)
Wherein, T
srepresent Static Air Temperature, unit is degree Celsius, T
trepresent total Air Temperature, unit is degree Celsius, and M represents Mach number.
Step 9, Kalman filtering.
Digital signal processing module, the Kalman filtering algorithm of the constant accelerator model that barometer altitude, rising or falling speed, rising or falling speed rate of change adopt is referred to: normal Fast track surgery correspond to aircraft and does uniformly accelrated rectilinear motion, barometer altitude, rising or falling speed and rising or falling speed rate of change are considered as state vector, wherein the transient change of rising or falling speed rate of change is considered as random disturbance, barometer altitude is considered as measure vector.
Adopt the Kalman filtering algorithm parameter arranged in step 1, use Kalman filtering algorithm, obtain the aircraft state vector upgraded.The computing formula upgrading barometer altitude, rising or falling speed and rising or falling speed rate of change is as follows:
H＝X
1(0)，V
H＝X
1(1)，ΔV
H＝X
1(2)
Wherein, H represents the barometer altitude of renewal, V
hrepresent the barometer altitude of aircraft increase p.s., i.e. rising or falling speed; Δ V
hrepresent the rising or falling speed of aircraft increase p.s., i.e. rising or falling speed rate of change, Δ represents variable quantity.X
1represent the aircraft state vector upgraded, X
1(0), X
1(1), X
1(2) three elements of the aircraft state vector of renewal are represented respectively.
Step 10, sends data and failure code.
Atmosphere data and failure code, by address bus and data bus, are sent to time-sequence control module by digital signal processing module.
Step 11, judges whether to receive data and failure code.
Time-sequence control module judges whether the atmosphere data and the failure code that receive digital signal processing module transmission, if the data of receiving and failure code, then time-sequence control module sends to digital signal processing module answer signal, returns and performs step 2; Otherwise, return and perform step 10.
Claims (3)
1., based on an air data computer for Kalman filtering algorithm, comprise sensor assembly, time-sequence control module and digital signal processing module; It is characterized in that:
Described sensor assembly comprises digital pressure sensor and analog temperature sensor, and described digital pressure sensor is connected with time-sequence control module respectively with analog temperature sensor; Digital pressure sensor inside is containing two analog to digital converters, under the control of time-sequence control module, two analog to digital converters export static pressure digital signal and total head digital signal respectively, static pressure digital signal and total head digital signal are through amplification, gating, after sending into time-sequence control module process, obtain static pressure data and total head data; The temperature analog signal that described analog temperature sensor exports, after amplification, gating and A/D conversion, is sent into time-sequence control module process, is obtained temperature data;
Described time-sequence control module, by Control timing sequence signal, completes the communication with digital signal processing module; Time-sequence control module sends a look-at-me every 50ms to digital signal processing module; Static pressure digital signal, total head digital signal and airport static pressure data that time-sequence control module reception digital pressure sensor exports and the temperature analog signal that analog temperature sensor exports, by address bus and data bus successively by static pressure data, total head data, airport static pressure data and temperature data, send to digital signal processing module, and judge whether the atmosphere data and the failure code that receive digital signal processing module transmission;
Described digital signal processing module is connected by address bus and data bus with time-sequence control module, completes the transmission between data; Digital signal processing module, to the parameter in analog temperature sensor coefficient, Kalman filtering algorithm, receive data address and need the atmosphere data being sent to time-sequence control module to carry out initialization; Digital signal processing module judges whether the look-at-me receiving time-sequence control module transmission, if the look-at-me of receiving, then after digital signal processing module response look-at-me, received the static pressure data, total head data, temperature data and the airport static pressure data that are sent by time-sequence control module by address bus and data bus; Digital signal processing module judges whether the temperature data received exceeds-40 DEG C ~ 70 DEG C ambient temperature ranges set by analog temperature sensor; After digital signal processing module carries out data prediction to the temperature data received, static pressure data and total head data, calculate atmosphere data; Digital signal processing module adopts the Kalman filtering algorithm of constant accelerator model to upgrade barometer altitude, rising or falling speed, rising or falling speed rate of change; Atmosphere data and failure code, by address bus and data bus, are sent to time-sequence control module by digital signal processing module;
Described barometer altitude refers to the height of aircraft apart from standard pressure plane, and standard pressure plane refers to the mean sea level that standard state is 760 mm Hg, temperature is 288.15 Kelvins, density is 1.225 kilograms per cubic meter; Described rising or falling speed refers to the barometer altitude of aircraft increase p.s.; Described rising or falling speed rate of change refers to the rising or falling speed of aircraft increase p.s..
2., based on an air data computer implementation method for Kalman filtering algorithm, comprise the steps:
(1) initialization:
Digital signal processing module, to the parameter in analog temperature sensor coefficient, Kalman filtering algorithm, receive data address and need the atmosphere data being sent to time-sequence control module to carry out initialization;
(2) look-at-me is sent:
Time-sequence control module, by Control timing sequence signal, sends a look-at-me every 50ms to digital signal processing module;
(3) judge whether to receive look-at-me:
Digital signal processing module judges whether the look-at-me receiving time-sequence control module transmission, if the look-at-me of receiving, then, after digital signal processing module response look-at-me, performs step (4); If do not receive look-at-me, then return and perform step (2);
(4) data are sent:
Static pressure digital signal, total head digital signal and airport static pressure data that time-sequence control module reception digital pressure sensor exports and the temperature analog signal that analog temperature sensor exports, by address bus and data bus successively by static pressure data, total head data, temperature data and airport static pressure data, send to digital signal processing module;
(5) data are received:
Digital signal processing module receives the static pressure data, total head data, temperature data and the airport static pressure data that are sent by time-sequence control module;
(6) temperature data whether over range is judged:
Digital signal processing module judges whether the temperature data received exceeds-40 DEG C ~ 70 DEG C ambient temperature ranges set by analog temperature sensor, if exceeded, performs step (10); Otherwise, perform step (7);
(7) data prediction:
(7a) digital signal processing module is to the temperature data received, and removes maximal value wherein and minimum value respectively, and residuals temperatures data are got average, obtains pretreated temperature data;
(7b) digital signal processing module gets average to the static pressure data received and total head data respectively, obtains pretreated static pressure data and total head data;
(8) atmosphere data is calculated:
(8a) according to the following formula, calculating needs the total Air Temperature being sent to time-sequence control module:
T
T＝kT
p+b
Wherein, T
trepresent and need the total Air Temperature being sent to time-sequence control module, described total Air Temperature refers to that in aircraft flight, air is compressed the atmospheric temperature at rear stagnation point place, T
prepresent pretreated temperature data, k, b represent as the straight slope corresponding to the correction factor of analog temperature sensor and intercept respectively;
(8b) digital signal processing module, to the static pressure data after data prediction and total head data, according to the computing formula provided in selected digital pressure sensor handbook, obtains and needs the air static pressure and the air total head that are sent to time-sequence control module; Described air static pressure refers to that aircraft flight face overdraught is not by the atmospheric pressure of disturbance place; Described air total head refers to that aircraft is on the aircraft surfaces just to air motion direction, the pressure recorded when air-flow is obstructed completely;
(8c) digital signal processing module, the total Air Temperature of time-sequence control module, air static pressure, air total head and airport static pressure data will be needed to be sent to, as known atmosphere data parameter, the pressure-height formula of adopting international standards under air, obtains barometer altitude, relative barometric pressure height, rising or falling speed, rising or falling speed rate of change, indicator air speed, indicator air speed rate of change, true air speed, Mach number, large Pneumatic pressure, Static Air Temperature;
Described barometer altitude refers to the height of aircraft apart from standard pressure plane, and standard pressure plane refers to the mean sea level that standard state is 760 mm Hg, temperature is 288.15 Kelvins, density is 1.225 kilograms per cubic meter;
It is reference plane that described relative barometric pressure height refers to the airport ground level before taking off, the height that the center of gravity of airplane represents relative to this reference field and with gravity potential height;
Described rising or falling speed refers to the barometer altitude of aircraft increase p.s.;
Described rising or falling speed rate of change refers to the rising or falling speed of aircraft increase p.s.;
Described indicator air speed refers to the value of true air speed naturalization to standard pressure plane;
Described indicator air speed rate of change refers to the indicator air speed of aircraft increase p.s.;
Described true air speed refers to the speed of the relative windstream of aircraft, is the true velocity of aircraft relative to air movement;
Described Mach number refers to the ratio of true air speed and place level air middle pitch velocity of wave propagation;
Described large Pneumatic pressure refers to that desirable incompressible gas acts on the power in unit area when arriving stationary point, is the difference of air total head and air static pressure;
Described Static Air Temperature refers to atmospheric temperature undisturbed in aircraft flight around;
(9) Kalman filtering:
Digital signal processing module, to barometer altitude, rising or falling speed, rising or falling speed rate of change, adopts the Kalman filtering algorithm of constant accelerator model, obtains the barometer altitude, rising or falling speed and the rising or falling speed rate of change that upgrade;
(10) data and failure code is sent:
Atmosphere data and failure code, by address bus and data bus, are sent to time-sequence control module by digital signal processing module;
(11) judge whether to receive data and failure code:
Time-sequence control module judges whether the atmosphere data and the failure code that receive digital signal processing module transmission, if the data of receiving and failure code, then time-sequence control module sends to digital signal processing module answer signal, returns and performs step (2); Otherwise, return and perform step (10).
3. the air data computer implementation method based on Kalman filtering algorithm according to claim 2, is characterized in that, the initialized concrete steps described in step (1) are as follows:
The first step, under analog temperature sensor being placed in-40 DEG C ~ 70 DEG C environment temperatures, records input value and the output valve of one group of analog temperature sensor, records 23 groups of temperature datas altogether every 5 DEG C; Least square method is utilized to simulate straight line to 23 groups of temperature datas respectively, using the slope of straight line and the intercept correction factor as analog temperature sensor;
Second step, is set to the correction factor of analog temperature sensor by analog temperature sensor coefficient;
3rd step, in digital signal processing module, adopts Kalman's constant accelerator model, sets the parameter in Kalman filtering algorithm;
4th step, receives the address of data by digital signal processing module, send the address of data with time-sequence control module, is set to same address;
5th step, is set to zero by needing the atmosphere data value being sent to time-sequence control module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410105051.0A CN103869383B (en) | 2014-03-20 | 2014-03-20 | Based on air data computer and its implementation of Kalman filtering algorithm |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410105051.0A CN103869383B (en) | 2014-03-20 | 2014-03-20 | Based on air data computer and its implementation of Kalman filtering algorithm |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103869383A CN103869383A (en) | 2014-06-18 |
| CN103869383B true CN103869383B (en) | 2016-03-02 |
Family
ID=50908115
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410105051.0A Expired - Fee Related CN103869383B (en) | 2014-03-20 | 2014-03-20 | Based on air data computer and its implementation of Kalman filtering algorithm |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103869383B (en) |
Families Citing this family (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104238417A (en) * | 2014-09-15 | 2014-12-24 | 西安电子科技大学 | Digital atmosphere data computer and implementation method thereof |
| CN106814409A (en) * | 2015-12-02 | 2017-06-09 | 协调工程企业股份有限公司 | Can Bluetooth communication meteorological observation device |
| CN105606071A (en) * | 2016-03-03 | 2016-05-25 | 成都仁颐越立科技有限公司 | Atmospheric pressure altimeter based on GPS positioning and temperature correcting and correcting method |
| CN106950002A (en) * | 2017-02-24 | 2017-07-14 | 中国航天空气动力技术研究院 | A kind of Flush Airdata Sensing System |
| CN109062246B (en) * | 2018-07-23 | 2021-11-09 | 南京理工大学 | Modularized flight control system with multitask self-scheduling function and design method thereof |
| CN111504341B (en) * | 2020-04-30 | 2023-09-19 | 中国直升机设计研究所 | Helicopter flight state identification method |
| CN112545521B (en) * | 2020-12-02 | 2023-06-30 | 中国人民解放军海军特色医学中心 | Design method of portable muscle strength dual-sensing filtering high-precision measuring device |
| CN113280834B (en) * | 2021-05-24 | 2022-11-11 | 北京安达维尔民用航空技术有限公司 | Airplane comprehensive backup electronic instrument system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102360088A (en) * | 2011-09-09 | 2012-02-22 | 陕西长岭电子科技有限责任公司 | Air data computer and realization method thereof |
| CN202281840U (en) * | 2011-09-15 | 2012-06-20 | 陕西长岭电子科技有限责任公司 | Air data computer |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090319189A1 (en) * | 2008-06-23 | 2009-12-24 | Honeywell International Inc. | Low cost, unattended weather sensor |
-
2014
- 2014-03-20 CN CN201410105051.0A patent/CN103869383B/en not_active Expired - Fee Related
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102360088A (en) * | 2011-09-09 | 2012-02-22 | 陕西长岭电子科技有限责任公司 | Air data computer and realization method thereof |
| CN202281840U (en) * | 2011-09-15 | 2012-06-20 | 陕西长岭电子科技有限责任公司 | Air data computer |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103869383A (en) | 2014-06-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103869383B (en) | Based on air data computer and its implementation of Kalman filtering algorithm | |
| EP3032290B1 (en) | Method and system for forescating weather using atmospheric water content measured onboard an aircraft | |
| Fichtl et al. | Longitudinal and lateral spectra of turbulence in the atmospheric boundary layer at the Kennedy Space Center | |
| CN102360088B (en) | Air data computer and realization method thereof | |
| CN103257348A (en) | Measurement system of relative altitude and relative attitude of air vehicle and measurement method thereof | |
| CN103994754A (en) | Altitude measuring method and system | |
| US10106267B2 (en) | Enhancing engine performance to improve fuel consumption based on atmospheric ice particles | |
| CN101950017B (en) | Emulation method of high fidelity onboard foresight weather radar low-altitude wind shear signal | |
| Jensen et al. | The Midlatitude Continental Convective Clouds Experiment (MC3E) sounding network: operations, processing and analysis | |
| CN105628051A (en) | Embedded atmosphere measuring equipment performance evaluation method | |
| CN105300387A (en) | Nonlinear non-Gaussian ranking filtering method for Martian atmosphere entering section | |
| CN113609639B (en) | Evaporation waveguide correction method suitable for stable condition | |
| US20220196878A1 (en) | Program product for creating weather prediction data, a method for creating weather prediction data, and a moving vehicle | |
| CN201887775U (en) | Simulation system for radio altitude echoed signals | |
| Majeed et al. | Multi sensor data fusion based approach for the calibration of airdata systems | |
| Johnston et al. | A study of flush air data system calibration using numerical simulation | |
| Frew et al. | Toward an Autonomous Airborne Scientist for Studying Severe Local Storms | |
| Reasor Jr et al. | Numerical predictions of static-pressure-error corrections for a modified T-38C aircraft | |
| Croke et al. | 8.5 PRELIMINARY VERIFICATION OF THE NCAR-AIRDAT OPERATIONAL RTFDDA-WRF SYSTEM | |
| CN206019700U (en) | A kind of Satellite Formation Flying earth atmosphere detection system based on gps signal | |
| Krishna et al. | A method for accurate estimation of altitude in re-entry vehicles using flush air data sensing system (FADS) | |
| Awange et al. | GPS meteorology in environmental monitoring | |
| Wilfong, Sr et al. | Upper air data systems to support space launch range activities | |
| Hacker | Refractive Turbulence-Measurements and Analysis | |
| Uvah | A Framework for Dynamical True Altitude Modeling in Aviation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20160302 Termination date: 20210320 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |