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When the system model and noise statistical characteristics are known, the conventional Kalman filtering algorithm is suitable. In most cases, the noise statistics are unknown. To improve the alignment precision and convergence speed of strap-down inertial navigation system, an initial alignment method based on Sage-Husa adaptive filter is proposed. Automatic on-line estimation and correction for...
An interferometric fiber optic Gyroscope (IFOG) is a core component in the inertial navigation system (INS), and used to measure the rotation rate of an object based on Sagnac principle. The output of IFOG suffers with noise and random drift errors, due to the variation and fluctuations of the ambient temperature during the operation time. Random drift error is the main source of error and it degrades...
This work considers the problem of tracking multiple sources using observations acquired at spatially scattered sensors and under power constraints. The Kaiman filtering minimization formulation is extended with norm-one regularization terms and a power constraint. The resulting minimization formulation is capable to associate sources with sensors, and track the unknown sources while adhering to the...
Exploiting non-renewable energy to fulfill the huge demand of human race is an ever increasing burden on the atmosphere of the earth. To lessen this burden several renewable energy sources are used - one of which is photovoltaic energy. The source of solar /photovoltaic energy is the radiation of the sun which is abundant in nature. A solar cell produces electric energy when sunlight is incident on...
The vehicle state is of significant to examine and control vehicle performance. But some vehicle states such as vehicle velocity and side slip angle which are vital to active safety application of vehicle can not be measured directly and must be estimated instead. In this paper, a Cubature Kalman Filter (CKF) based algorithm for estimation vehicle velocity, yaw rate and side slip angle using steering...
In this paper, is proposed a robust sensorless speed observer-controller scheme for a Permanent Magnet Synchronous Motor (PMSM) based on the use of an Extended Kalman Filter (EKF) to estimate both position and speed, without any mechanical sensor. Then, a state-feedback optimal control algorithm is developed for uncertain of PMSM, based on the use of an Algebraic Riccati Equation (ARE) and a convex...
A novel Kaiman filter to estimate position of a biped robot is proposed. It combines the kinematics and the double-integral of acceleration, only using internal sensors and achieving high-rate estimation. The kinematics computation is rooted to the anchoring pivot, which is the most invariant point in the foot with respect to the ground. The idea is the same with the authors previous method, but the...
The SITAN algorithm makes use of terrain elevation information to aid inertial navigation system and achieves good results. The geomagnetic field can be used as the conditions of the auxiliary inertial navigation, because the geomagnetic value map and the terrain elevation map have high similarity. By using the SITAN algorithm and combining the contour information of existed geomagnetic map with the...
This paper describes a self-balancing mobile robot and their principal features as materials of construction, instrumentation, data communication and control. This kind of robots are an excellent platform for testing different techniques of control due to characteristics of the system (unstable, underactuated). The tilt measurement by means of an Accelerometer-Gyro pair to control a two-wheeled, self-balancing...
A speed and flux estimation method of induction motors using fuzzy extended kalman filter(FEKF) is proposed in this paper, which is used to make lower impact of time varied statistic of measurement noise. It reaches a better speed estimation accuracy of induction motors than the extended kalman filter(EKF). The proposed algorithm modifies the measurement noise covariance of extended kalman filter...
In this paper, a filtering performance degradation problem of the globally optimal unbiased minimum-variance filter (GOUMVF) for systems with unknown inputs has been explored. The main problem encountered in the GOUMVF lies in the fact that its gain matrix is in some degeneration forms, which are defined as those that are not fully connected to the process noise and the measurement noise covariances;...
The tracking performance of the Kalman filter (KF) for the downlink extra-fine synchronization sequence that supports high data rate (2.048 Mbps), transmitted by the Enhanced Polar System (EPS) in Molniya orbits, is investigated in the paper. At the receiver, a KF is used to track the range and range rate of the payload to estimate the payload clock and Doppler error. The tracking performance of the...
The propagated sound waves in an indoor environment hit the surfaces of solid objects and produce reverberant speech signals. Reverberated speech signals in noisy acoustical environments cause some problems such as reducing speech intelligibility, distinguishing speakers, locating source, quality for hands-free telephony, hearing aid, etc. Adaptive filters can be applied to suppress the interfering...
This paper discusses the state estimation task in the Van der Vusse reaction, which is a classical benchmark in a number of control studies in chemistry. Recently, it was shown that the extended Kalman filter is not able to estimate accurately the concentrations in this reaction on the basis of temperature measurements, only. Here, we demonstrate that modern state estimation methods, such as the continuous-discrete...
The integral-free Kalman filters which are widely used in target tracking are studied. The algorithms of Unscented Kalman filter (UKF), Cubature Kalman filter (CKF) and Square-root cubature Kalman filter (SCKF) are compared in details. A modified algorithm (MSCKF) is proposed to optimize the performance. When considering different original ranges and radial speeds, simulation of linear motion targets...
Photoplethysmography (PPG) can be carried out through facial video recording by a smart phone camera in ambient light. The main challenge is to eliminate motion artifacts and ambient noise. We describe a real-time algorithm to quantify the heart beat rate from facial video recording captured by the camera of a smart phone. We extract the green channel from the video. Then we normalize it and use a...
In this paper, a linear unbiased minimum-variance filtering problem is considered for a class of systems with randomly multi-step sensor delays. A new mathematical model is established for the multi-step sensor delays. Different from the augmented method for dealing with delayed systems, a linear unbiased minimum-variance filter design method is proposed without augmenting the state vector, which...
In the field of maneuvering target tracking, the performance of Kalman filter and its improved algorithms depends on the accuracy of pre-designed process noise statistics. When the pre-designed process noise statistics do not match with the actual situation, it will be difficult to obtain a good filtering performance. But unbiased finite impulse response (UFIR) filter does not need the prior knowledge...
The most crucial problem in navigation system is localization. The global positioning system (GPS) has long been used in mobile unit localization. However, GPS is incapable in some situation such as indoor environment. The received signal strength indicator (RSSI) from wireless communication is a promising alternative method to derive the location of a mobile unit. To improve the precision and robustness...
Reliable knowledge of position and orientation is a prerequisite for many applications regarding unmanned navigation, mapping, or environmental modeling. GNSS-aided inertial navigation is the preferred solution for outdoor applications with the well-known weaknesses and limitations. In order to overcome these, alternative technologies have to be investigated and developed. Therefore a stereo-vision-aided...
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