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Provided are an integrated navigation apparatus and a method for providing navigation information using the same. The integrated navigation apparatus includes a first filter, a second filter, a mode probability updating unit, a first navigation information calculating unit, a second navigation infor

Provided are an integrated navigation apparatus and a method for providing navigation information using the same. The integrated navigation apparatus includes a first filter, a second filter, a mode probability updating unit, a first navigation information calculating unit, a second navigation information calculating unit, a fusion unit and a navigation information fusion unit.

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1. An integrated navigation apparatus provided with a GPS receiver receiving GPS satellites signals and an inertial measurement unit (IMU) having a 3-axis accelerometer calculating a motion distance of a moving object and a 3-axis gyro measuring a rotation of the moving object, comprising: a filteri

1. An integrated navigation apparatus provided with a GPS receiver receiving GPS satellites signals and an inertial measurement unit (IMU) having a 3-axis accelerometer calculating a motion distance of a moving object and a 3-axis gyro measuring a rotation of the moving object, comprising: a filtering means for outputting a first state variable estimation value and a second state variable estimation value for error compensation of an INS navigation information based on measurement data inputted from the GPS receiver and error covariances of a first filter and a second filter, calculating and outputting a mode probability for fusing navigation information, performing fusing onto the first filter and the second filter by calculating a fusion probability based on the mode probability and a Markov transition matrix, and outputting fused state variables as fusion results of first navigation information and second navigation information; andan inertial navigation calculating means for calculating first INS navigation information and second INS navigation information based on measurement data of the IMU, transmitting the first INS navigation information and the second INS navigation information to the filtering means, compensating the first INS navigation information and the second INS navigation information based on the first state variable estimation value and the second state variable estimation value inputted from the filtering means, transmitting the compensated first INS navigation information and the compensated second INS navigation information to the filtering means, compensating the first navigation information and the second navigation information based on the fused state variables inputted from the filtering means in response to a compensated results of the first INS navigation information and the second INS navigation information, fusing the compensated first navigation information and the compensated second navigation information based on the mode probability inputted from the filtering means to thereby produce fused navigation information, and providing the fused navigation information to a display unit. 2. The integrated navigation apparatus as recited in claim 1, wherein the first filter is an infinite impulse response (IIR) filter. 3. The integrated navigation apparatus as recited in claim 2, wherein the second filter is a finite impulse response (FIR) filter. 4. An integrated navigation apparatus provided with a GPS receiver receiving GPS satellites signals and an inertial measurement unit (IMU) having a 3-axis accelerometer calculating a motion distance of a moving object and a 3-axis gyro measuring a rotation of the moving object, comprising: a first filter and a second filter for providing state variable estimation values in order to compensate navigation information for an error based on measurement data inputted from the GPS receiver and an error covariance and outputting a residual of filter and a residual covariance for updating a mode probability;a mode probability updating means for calculating a likelihood ratio based on the residual of filter and the residual covariance, updating the mode probability based on the acquired likelihood ratio, outputting the updated mode probability, and calculating and acquiring a fusion probability based on the updated mode probability and a Markov transition matrix;a first navigation information calculating means and a second navigation information calculating means for generating INS navigation information based on information inputted from the IMU, transmitting the INS navigation information to the first filter and the second filter, respectively, compensating the INS navigation information based on the state variable estimation values inputted from the first filter and the second filter, compensating the navigation information based on a fused state variable, and outputting the compensated navigation information;a fusion means for fusing the compensated navigation information inputted from the first navigation information calculating means and the second navigation information calculating means based on the fusion probability inputted from the mode probability updating means, providing the fused state variable to the first navigation information calculating means and the second navigation information calculating means, fusing the error covariances inputted from the first filter and the second filter based on the fusion probability, and providing the fused error covariance matrix to the first filter and the second filter; anda navigation information fusion means for fusing the navigation information inputted from the first navigation information calculating means and the second navigation information calculating means based on the mode probability inputted from the mode probability updating means and outputting fused navigation information. 5. The integrated navigation apparatus as recited in claim 4, wherein the first filter is an infinite impulse response (IIR) filter. 6. The integrated navigation apparatus as recited in claim 5, wherein the second filter is a finite impulse response (FIR) filter. 7. The integrated navigation apparatus as recited in claim 4, wherein the mode probability updating means initializes the Markov transition matrix, the fusion probability and a normalization factor before executing the first filter and the second filter. 8. The integrated navigation apparatus as recited in claim 4, wherein the mode probability updating means calculates the likelihood ratio based on an Equation expressed as: Λj,k=12⁢π⁢Sj,k⁢exp⁢{-12⁢rj,kT⁢Sj,k-1⁢rj,k},where rj,k represents the residual when k time and j filter; Sj,k is the residual covariance; T denotes a transpose of vector; the residual of the filter is calculated based on rj,k=zk−{circumflex over (z)}j,k; the residual covariance is calculated based on Sj,k=Hj,kPj,k−Hj,kT+Rj; zk is the GPS measurement data; {circumflex over (z)}j,k is an estimation value of the navigation information; H is a measurement matrix; P is a covariance of a state variable; and R is an error covariance of the measurement data. 9. The integrated navigation apparatus as recited in claim 4, wherein the mode probability updating means calculates the likelihood ratio based on an Equation expressed as: Λj,k=12⁢π⁢Sj,k⁢exp⁢{-12⁢Aj,k},⁢WhereAj,k=1k⁢∑i=1k⁢rj,iT⁢Sj,i-1⁢rj,i. 10. The integrated navigation apparatus as recited in claim 8, wherein the mode probability updating means updates the mode probability based on an Equation expressed as: μj,k=1c⁢Λj,k⁢c_j,⁢wherec=∑i=12⁢Λj,k⁢c_i; and cj is the normalization factor. 11. The integrated navigation apparatus as recited in claim 10, wherein the mode probability updating means calculates the fusion probability based on the updated mode probability and the Markov transition matrix (Mij) as an Equation expressed as: μij,k=1∑i=12⁢Mij⁢μi,k⁢Mij⁢μi,k. 12. The integrated navigation apparatus as recited in claim 11, wherein the fusion means calculates and acquires the fused state variable {circumflex over (x)}j,k0 based on error-compensated navigation results {circumflex over (x)}j,k inputted from the first INS calculating means and the second INS calculating means and the fusion probability μij,k as an Equation expressed as: x^j,k0=∑i=12⁢x^i,k⁢μij,k,and the fusion means calculates a fused error covariance matrix for feedback to the first filter and the second filter based on the error covariance inputted from the first filter and the second filter, the error-compensated navigation results {circumflex over (x)}j,k inputted from the first INS calculating means and the second INS calculating means, the fused state variable {circumflex over (x)}j,k0 and the fusion probability μij,k as an Equation expressed as: Pj,k0=∑i=12⁢{Pi,k+[x^i,k-x^j,k0]⁡[x^i,k-x^j,k0]T}⁢μij,k. 13. A method for providing navigation information in an integrated navigation apparatus having an inertial measurement unit (IMU) and a GPS receiver, comprising the steps of: a) calculating a first state variable estimation value and a second state variable estimation value for compensating navigation information for an error based on a measurement data inputted from the GPS receiver and an error covariance;b) calculating a likelihood ratio based on residual of filter and a residual covariance, updating a mode probability based on the acquired likelihood ratio, calculating and acquiring a fusion probability based on the updated mode probability and a Markov transition matrix;c) compensating a first INS navigation information and a second INS navigation information based on the first state variable estimation value and the second state variable estimation value acquired in step a);d) fusing the compensated first INS navigation information and the compensated second INS navigation information compensated in step c) based on the fusion probability acquired in step b), acquiring a fused state variable, fusing the error covariance of the filter based on the fusion probability, and outputting a fused error covariance matrix for updating the error covariance of the filter;e) compensating a first navigation information and a second navigation information based on the fused state variable acquired in step d) and outputting a compensated first navigation information and a compensated second navigation information; andf) fusing the compensated first navigation information and the compensated second navigation information based on the updated mode probability updated in step b). 14. The method as recited in claim 13, further comprising the step of: a0) initializing the Markov transition matrix, the mode probability and a normalization factor before the step a). 15. The method as recited in claim 14, wherein the first state variable estimation value and the second state variable estimation value are calculated based on an infinite impulse response (IIR) filter and a finite impulse response (FIR) filter, respectively. 16. The method as recited in claim 13, wherein the likelihood ratio of the step b) is calculated based on an Equation expressed as: Λj,k=12⁢π⁢Sj,k⁢exp⁢{-12⁢rj,kT⁢Sj,k-1⁢rj,k},where rj,k represents the residual when k time and j filter; Sj,k is the residual covariance; T denotes a transpose of vector; the residual of the filter is calculated based on rj,k=zk−{circumflex over (z)}j,k; the residual covariance is calculated based on Sj,k=Hj,kPj,k−Hj,kT+Rj; zk is the GPS measurement data; {circumflex over (z)}j,k is an estimation value of the navigation information; H is a measurement matrix; P is a covariance of a state variable; and R is an error covariance of the measurement data. 17. The method as recited in claim 13, wherein the likelihood ratio of the step b) is calculated based on an Equation expressed as: Λj,k=12⁢π⁢Sj,k⁢exp⁢{-12⁢Aj,k},⁢whereAj,k=1k⁢∑i=1k⁢rj,iT⁢Sj,i-1⁢rj,i. 18. The method as recited in claim 14, wherein the mode probability of the step b) is updated based on an Equation expressed as: μj,k=1c⁢Λj,k⁢c_j,⁢wherec=∑i=12⁢Λj,k⁢c_i; and cj is the normalization factor. 19. The method as recited in claim 18, wherein the fusion probability of the step b) is calculated and acquired based on the updated mode probability and the Markov transition matrix (Mij) as an Equation expressed as: μij,k=1∑i=12⁢Mij⁢μi,k⁢Mij⁢μi,k. 20. The method as recited in claim 19, wherein the fused state variable {circumflex over (x)}j,k0 is calculated and acquired based on error-compensated navigation result {circumflex over (x)}j,k and the fusion probability μij,k as shown in an equation expressed as: x^j,k0=∑i=12⁢x^i,k⁢μij,k,and a fused error covariance matrix is calculated and acquired based on the error covariances inputted from the first filter and the second filter, the error-compensated navigation result {circumflex over (x)}j,k, the fused state variable {circumflex over (x)}j,k0 and the fusion probability μij,k as shown in an equation expressed as: Pj,k0=∑i=12⁢{Pi,k+[x^i,k-x^j,k0]⁡[x^i,k-x^j,k0]T}⁢μij,k.