GPS receiver SPS accuracy assessment using LS and LQ estimators for precise navigation

Laveti, Ganesh; Rao, G. Sasibhushana; Rani, K. Jhansi; Nalinee, A.; Babu, A. Mahesh

doi:10.1109/indicon.2014.7030411

Cited by 12 publications

(5 citation statements)

References 4 publications

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“…The presented work is depicted in 1. The performance analysis is based on 2D position accuracy measures and 3D accuracy measures [1], which are listed in 1.…”

Section: Search and Rescue Optimization (Sar)mentioning

confidence: 99%

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Performance Analysis of Computational Intelligence Correction

Arasavali

Gottapu

2021

Preprint

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Kalman ﬁlter (KF) is a widely used navigation algorithm, especially for precise positioning applications. However, the exact ﬁlter parameters must be deﬁned a priori to use standard Kalman ﬁlters for coping with low error values. But for the dynamic system model, the covariance of process noise is a priori entirely undeﬁned, which results in diﬃculties and challenges in the implementation of the conventional Kalman ﬁlter. Kalman Filter with recursive covariance estimation applied to solve those complicated functional issues, which can also be used in many other applications involving Kalaman ﬁltering technology, a modiﬁed Kalman ﬁlter called MKF-RCE. While this is a better approach, KF with SAR tuned covariance has been proposed to resolve the problem of estimation for the dynamic model. The data collected at (x: 706970.9093 m, y: 6035941.0226 m, z: 1930009.5821 m) used to illustrate the performance analysis of KF with recursive covariance and KF with computational intelligence correction by means of SAR (Search and Rescue) tuned covariance, when the covariance matrices of process and measurement noises are completely unknown in advance.

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“…The presented work is depicted in 1. The performance analysis is based on 2D position accuracy measures and 3D accuracy measures [1], which are listed in 1.…”

Section: Search and Rescue Optimization (Sar)mentioning

confidence: 99%

“…It is the primary module for the Kalman Filter's measurement Update and State Update [19]. Suppose the state of x k to be predicted is regulated by the following dynamics (1).…”

mentioning

confidence: 99%

Performance Analysis of Computational Intelligence Correction

Arasavali

Gottapu

2021

Preprint

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“…The accuracy of the unknown target in the position estimated ( x, y) is influenced by environment and various system factors for example sensor geometry, system noise, sensor position error and measurement error (measurement uncertainty). Though, the outcome due to noise and other factors can be decreased by using different error mitigation techniques [53] and algorithms for the positioning [54]. The effect due to the geometry of the sensor can only be reduced by choosing the best placement of sensors [55].…”

Section: Geometric Dilution Of Precision (Gdop)mentioning

confidence: 99%

A Hybrid Access Control Model With Dynamic COI for Secure Localization of Satellite and IoT-Based Vehicles

et al. 2020

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Secure localization of vehicles is gaining the attention of researchers from both academia and industry especially due to the emergence of internet of things (IoT). The modern vehicles are usually equipped with circuitries that gives connectivity with other vehicles and with cellular networks such as 4G/Fifth generation cellar network (5G). The challenge of secure localization and positioning is magnified further with the invention of technologies such as autonomous or driverless vehicles based on IoT, satellite, and 5G. Some satellite and IoT based localization techniques exploit machine learning, semantic segmentation, and access control mechanism. Access control provides access grant and secure information sharing mechanism to authorized users and restricts unauthorized users, which is necessary regarding security and privacy of government or military vehicles. Previously, static conflict of interest (COI) based access control was used for security proposes. However, static COI based access control creates excesses and administrative overload that creates latency in execution, which is the least tolerable factor in modern IoT or 5G control vehicles. Therefore, in this paper, a hybrid access control (HAC) model is proposed that implements the dynamic COI in the HAC model on the level of roles. The proposed model is enhanced by modifying the role-based access control (RBAC) model by inserting new attributes of the RBAC entities. The HAC model deals with COI on the level of roles in an efficient manner as compared to previously proposed models. Moreover, this model features significant improvement in terms of dynamic behavior, decreased administrative load, and security especially for vehicular localization. Furthermore, the mathematical modeling of the proposed model is implemented with an example scenario to validate the concept. INDEX TERMS Access control, hybrid access control, secure vehicle localization, machine learning, neural networks, Internet of Things.

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“…Equation 1 need to be solved for the 3 unknowns x u ,y u and z u but due to the nonlinearity prevailed in the equation; direct method of solving will be a cumbersome process. Also the direct method for GPS need to find the reliable 3 satellite ranges before in hand, because for most of the time GPS will be overdetermined in nature [5] given in (3).…”

Section: Toa Measurement In Gpsmentioning

confidence: 99%

“…Mitigation of the atmospheric errors and system bias is possible on proper modeling of the biases, where as an optimal position estimator is needed in determining precise and accurate navigation solution [3]. However modeling of above said biases is beyond the scope of this paper and it deals with the implementation of the new navigation solution that provides accurate and precise solution for defence applications.…”

Section: Introductionmentioning

confidence: 99%

A Novel TOA measurement based global evolutionary search estimator for defence applications

Laveti

Rao

Kumar

et al. 2015

2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO)

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Time of Flight (TOF), popularly Time of Arrival (TOA) is the time a radio signal takes to reach the receiver from a remote transmitter. TOA measurements are broadly used for source localization and position fixing in civil and defence applications. The accuracy in position fix is primarily influenced by factors like error in TOA measurements and position estimation solution employed. Though the accuracy and precision in position estimate are acceptable to tens of meters in civil applications, there are radio-navigation systems like GPS in defense, demand mill-meter level accuracy. Defense systems like CAT I & II air craft landing, missile guidance and tracking need high precision in position estimate. This paper focuses in developing a new TOA based precise navigation solution, grown out from the inherent features of traditional Least Squares (LS) and Global Evolutionary Search (GES) Estimators. To validate the algorithm, real world data collected from Dual Frequency GPS (DFGPS) receiver located at IISC, Bangalore (Lat/Lon: 13.01 o N / 77.56 o E) is used and Position accuracy measuresCircular Error probable (CEP), Spherical Error probable (SEP), MRSE (Mean Radial Spherical Error) and Distance Root Mean Square (DRMS) are used to analyse the algorithm performance.

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GPS receiver SPS accuracy assessment using LS and LQ estimators for precise navigation

Cited by 12 publications

References 4 publications

Performance Analysis of Computational Intelligence Correction

Performance Analysis of Computational Intelligence Correction

A Hybrid Access Control Model With Dynamic COI for Secure Localization of Satellite and IoT-Based Vehicles

A Novel TOA measurement based global evolutionary search estimator for defence applications

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