FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W767487540> ?p ?o ?g. }

• W767487540 endingPage "2360" @default.
• W767487540 startingPage "2351" @default.
• W767487540 abstract "The conventional GPS tracking loop is optimal in Maximum likelihood Estimation (MLE), respectively. It well works in normal signal to noise ratio (SNR) and signal dynamics within the tracking loop bandwidth. But, when the receiver operates in high dynamic environment, discriminator linearity doesn t maintain and tracking loop error increase. In the previous rearch, several algorithms were proposed to overcome these problems such as EKF based tracking loop, grid method. In the previous paper [Gee, ENC 2005], LQG based GPS receiver tracking loop is developed using EKF and Linear Quadratic Regulator (LQR). The EKF estimate the range rate, code phase, carrier phase error and navigation bit from inphase and quadrature measurement. And LQR calculate the optimal DCO input using pre-calculated steady state feedback gain. It had good tracking performance than conventional tracking loop in normal condition because it is designed to consider correlation of code and carrier tracking loop. But there is problem about nonlinearity of measurement model as ever. 2351 ION GNSS 21st. International Technical Meeting of the Satellite Division, 16-19, September 2008, Savannah, GA. In this paper, LQG based GPS tracking loop is implemented using nonlinear filtering techniques, i.e. Unscented Kalman Filter (UKF) and Particle Filter (PF). Also, the implemented algorithm performance is evaluated and compared. In the EKF, the measurement equations are linearized to the first order Taylor series in order to apply the Kalman filter, which is supposed to linear Gaussian systems. Instead of truncating the nonlinear measurement equation the UKF and PF approximate the distribution of the state deterministically and randomly, with a finite set of samples, and then propagate these points or particles through the original nonlinear functions, respectively. Because the nonlinear functions are used without approximation, it provides the better performance. INTRODUCTION The code and the carrier tracking loop are the essential parts of the GNSS receiver. Usually the code tracking is implemented by the Delay Locked Loop (DLL) and the carrier tracking is implemented by the Phase Locked Loop (PLL) and/or the Frequency Locked Loop (FLL). The tracking loop consists of three parts in general: discriminator, loop filter and VCO. The loop filter is the main part of the tracking loop design to ensure good tracking performance. Although the carrier Doppler and code Doppler are generated by the same relative movement between the satellite and the user, often, the loop filters for the each tracking loop are designed separately and independently. Common design parameters for the loop filters are the loop bandwidth and the loop damping ratio. A usual choice for the damping ratio is 0.707. The loop filter order is often chosen by the expected dynamics of the Doppler. For examples, the 2nd or 3rd order loop filter is used for high dynamic environments [1, 2]. Sometimes, they are used in combined manner such as carrier aided code tracking, FLL, etc. One way of carrier aiding is to feed the carrier DCO value calculated by the FLL to the DLL with appropriate scaling of code carrier / f f . For better GNSS signal tracking performance, we need to design the FLL/DLL altogether optimally. In this paper we deal with the GPS C/A tracking loop optimization. First, it is shown that the DLL/FLL design can be shown as an optimal controller design problem. Specially, the well known 2nd order DLL/FLL is shown to be equivalent to the special case of the LQG controller, that is the combination of the Kalman filter and the output state feedback controller. Based on this fact, we can consider the code and carrier tracking problem as the two inputs two outputs control problem from the view point of control theory. The control objective is to minimize the total tracking error in carrier phase and code phase using two inputs, code and carrier DCO. The sate feedback control from the LQG design that is indeed a regulator will drive code and carrier DCO to track the incoming satellite signal with minimum mean squared tracking error. The tracking loop performance optimization could be done by the LQG design parameters tuning. First, the LQG control problem is introduced. The conventional design method for code and phase tracking loop is also reviewed. The tracking loop state space model will be derived and a LQG control problem for C/A code receiver tracking loop design is formulated and solved. COMBINED ESTIMATION AND CONTROL : LQG CONTROL Linear quadratic Gaussian (LQG) control refers to an optimal control problem where the plant model is linear, the cost function is quadratic, and the test conditions consist of random initial conditions, a white noise disturbance input, and a white measurement noise [3]. The system is described by the following linear state space model: 1 , ~ (0, ) , ~ (0, ) k k k k k f k k k k f N N + = + + = + x Fx Bu Gw w Q z Hx v v R (1) where k u is the control input and k w is a random disturbance input known as process noise. The measurements available for feedback are k z and k v is a random signal known as measurement noise. The process noise and measurement noise are assumed to be both white Gaussian and uncorrelated. Note that the description of the system and measurement noises is equivalent to that used in the Kalman filter problem. The system output to be controlled is k k = y Cx (2) A quadratic cost function including both this output and the control input is ( ) 1 ( , ) N T T k k k y k k c k k J E = ⎡ ⎤ = + ⎢ ⎥ ⎣ ⎦ ∑ x u y Q y u R u (3) where y Q , c R are positive definite. This cost function is frequently written directly in terms of the state: ( ) 1 ( , ) N T T k k k c k k c k k J E = ⎡ ⎤ = + ⎢ ⎥ ⎣ ⎦ ∑ x u x Q x u R u (4) where T c y = Q C Q C and c Q is positive semi-definite. 2352 ION GNSS 21st. International Technical Meeting of the Satellite Division, 16-19, September 2008, Savannah, GA. Fig 1. A LQG optimal control system A reasonable controller design for the LQG control problem can be obtained by using the linear quadratic regulator feedback gain matrix operating on the state estimation generated by the Kalman filter: ˆ k k = − u Kx (5) A block diagram of this feedback control system is given in Fig. 1. This control law is, in fact, the optimal solution to the LQG optimal control problem. The optimality of the control law (5) is called “the separation principle” in control theory. The state equations for the Kalman filter estimations are given by" @default.
• W767487540 created "2016-06-24" @default.
• W767487540 creator A5012496564 @default.
• W767487540 creator A5015849631 @default.
• W767487540 creator A5052415048 @default.
• W767487540 creator A5054791152 @default.
• W767487540 date "2008-09-19" @default.
• W767487540 modified "2023-09-23" @default.
• W767487540 title "Comparison of GPS Tracking Loop Performance in High Dynamic Condition with Nonlinear Filtering Techniques" @default.
• W767487540 cites W1548576912 @default.
• W767487540 cites W2123487311 @default.
• W767487540 cites W2124156864 @default.
• W767487540 cites W2132639726 @default.
• W767487540 cites W2953740964 @default.
• W767487540 hasPublicationYear "2008" @default.
• W767487540 type Work @default.
• W767487540 sameAs 767487540 @default.
• W767487540 citedByCount "0" @default.
• W767487540 crossrefType "journal-article" @default.
• W767487540 hasAuthorship W767487540A5012496564 @default.
• W767487540 hasAuthorship W767487540A5015849631 @default.
• W767487540 hasAuthorship W767487540A5052415048 @default.
• W767487540 hasAuthorship W767487540A5054791152 @default.
• W767487540 hasConcept C114614502 @default.
• W767487540 hasConcept C121332964 @default.
• W767487540 hasConcept C154945302 @default.
• W767487540 hasConcept C15744967 @default.
• W767487540 hasConcept C158622935 @default.
• W767487540 hasConcept C184670325 @default.
• W767487540 hasConcept C19417346 @default.
• W767487540 hasConcept C2775924081 @default.
• W767487540 hasConcept C2775936607 @default.
• W767487540 hasConcept C33923547 @default.
• W767487540 hasConcept C41008148 @default.
• W767487540 hasConcept C47446073 @default.
• W767487540 hasConcept C60229501 @default.
• W767487540 hasConcept C62520636 @default.
• W767487540 hasConcept C76155785 @default.
• W767487540 hasConceptScore W767487540C114614502 @default.
• W767487540 hasConceptScore W767487540C121332964 @default.
• W767487540 hasConceptScore W767487540C154945302 @default.
• W767487540 hasConceptScore W767487540C15744967 @default.
• W767487540 hasConceptScore W767487540C158622935 @default.
• W767487540 hasConceptScore W767487540C184670325 @default.
• W767487540 hasConceptScore W767487540C19417346 @default.
• W767487540 hasConceptScore W767487540C2775924081 @default.
• W767487540 hasConceptScore W767487540C2775936607 @default.
• W767487540 hasConceptScore W767487540C33923547 @default.
• W767487540 hasConceptScore W767487540C41008148 @default.
• W767487540 hasConceptScore W767487540C47446073 @default.
• W767487540 hasConceptScore W767487540C60229501 @default.
• W767487540 hasConceptScore W767487540C62520636 @default.
• W767487540 hasConceptScore W767487540C76155785 @default.
• W767487540 hasLocation W7674875401 @default.
• W767487540 hasOpenAccess W767487540 @default.
• W767487540 hasPrimaryLocation W7674875401 @default.
• W767487540 hasRelatedWork W1483276599 @default.
• W767487540 hasRelatedWork W1508196419 @default.
• W767487540 hasRelatedWork W2006980582 @default.
• W767487540 hasRelatedWork W2063496295 @default.
• W767487540 hasRelatedWork W2067107847 @default.
• W767487540 hasRelatedWork W2136179499 @default.
• W767487540 hasRelatedWork W2136325746 @default.
• W767487540 hasRelatedWork W2171818398 @default.
• W767487540 hasRelatedWork W2347762238 @default.
• W767487540 hasRelatedWork W2353832312 @default.
• W767487540 hasRelatedWork W2362966128 @default.
• W767487540 hasRelatedWork W2378266844 @default.
• W767487540 hasRelatedWork W2912295984 @default.
• W767487540 hasRelatedWork W2980986364 @default.
• W767487540 hasRelatedWork W3035103165 @default.
• W767487540 hasRelatedWork W3087368246 @default.
• W767487540 hasRelatedWork W3107680301 @default.
• W767487540 hasRelatedWork W3120297771 @default.
• W767487540 hasRelatedWork W3170948042 @default.
• W767487540 hasRelatedWork W3172803799 @default.
• W767487540 isParatext "false" @default.
• W767487540 isRetracted "false" @default.
• W767487540 magId "767487540" @default.
• W767487540 workType "article" @default.