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The nonlinearity estimation is a major problem in the application of Kalman filtering. Though EKF algorithm achieves the output estimation by using approximate nonlinear function, and it enhances the application in nonlinear system to some extent, for strong nonlinear systems, the EKF still has a large estimation error. Therefore, an approximate probability density of the UKF algorithm is proposed...
Power battery is the heart of electric vehicles, and the accurate state of charge (SOC) estimation is crucial for the management of the power battery. This paper proposes an adaptive strong tracking unscented Kalman filter (ASTUKF) algorithm to estimate the SOC of lithium-ion battery. This method doesn't need to compute the Jacobian matrix compared with the traditional strong tracking filter. This...
In order to maximize capacity utilization and guarantee safe operation of Li-ion battery pack, state-of-charge (SOC) inconsistency estimation is essential. And estimating cell electrochemical internal variables is also the requirement of next generation battery management system (BMS). However, it is challenging for the BMS in electric vehicles due to dynamic current conditions and limited computational...
In this paper, we propose an approach to distributed localization and motion control of unicycle mobile agents for the target circumnavigation problem. The bearing angle measurement-based localization performs when not all the agents get access to the target, but its performance is decided by the motion behaviors, and vice versa. Therefore we propose a coupled framework where we estimate the relative...
This paper presents an electrical parameter estimation method of the main-circuit insulation test for 1100kV gas insulated switchgear (GIS) equipment in order to realize the rationality of the test segmentation, equipment selection and parameter matching. First, the test method of main-circuit insulation is given. Then, the methods of estimating test capability of the variable-frequency series-resonant...
Particle impoverishment, which always leads to accuracy decreasing, is a classical problem of the traditional particle filter resampling. A particle filter resampling method based on improved genetic algorithm is proposed in this paper to solve the problem. In the improved algorithm, a genetic resampling step is applied for particle reproduction. The main work of the improved algorithm include two...
It is difficult to obtain failure data in stability analysis of long lifetime gyro such as hemispherical resonator gyro. Therefore, traditional stability analysis methods based on failure data is useless in stability analysis of long lifetime gyro. A stability analysis method based on probability statistics is proposed in this paper to solve this problem. In this method, Weibull distribution is applied...
In the AHRS using accelerometer can correct the error when calculating the attitude information of gyroscope. However, in the AHRS work process, the accelerometer measures the acceleration of gravity is affected by the external acceleration, and the accuracy is lost, which leads to the increase of the error of the attitude information. In order to estimate the external acceleration, this paper proposes...
Traffic retention is an important factor of intelligent transportation system, which can vividly reflect current state of the road. Accurate estimation of traffic retention can provide support for the dynamic allocation of the traffic signal, thus alleviating the problem of urban traffic congestion. The traditional method can only estimate the long-term or red light traffic retention according to...
Based on equivalent scatter center model of coning target, the micro-Doppler (m-D) signals induced by precession mainly consist of two components, i.e., cone node scatter signal varies in a sine and bottom scatter signal varies in a complex form time-frequency (TF) plane. As these two components are overlapped in the TF plane, this makes it hard to estimate the parameters of the target. Aiming at...
The DOA estimation problem for wideband signals has attracted much attention in the past years, and how to utilize and derive the common DOA information among frequency bins is the essential question. We address the wideband DOA estimation problem in this paper, and to solve this problem we propose a joint sparse Bayesian learning algorithm based on the sparse signal representation (SSR) of the covariance...
This paper introduces the basic theory and method of compressed sensing, and its application in DOA estimation. The theory uses a new sampling method through sparse sampling and reconstruction of the signal to break through the limitation of the Nyquist sampling theorem, effectively solving the inherent shortcomings of classic spatial spectrum estimation algorithms.
The speed of the target can be estimated by the sound pressure cross-correlation of the line spectrum of the moving target at different time intervals. However, a slight deviation of the line spectrum has a significant influence on the estimated result. In this paper this phenomenon is analyzed from the theory, then the speed of the target is estimated when the line spectrum is biased. Experimental...
A novel blind time-frequency joint synchronization based on the cyclostationary of orthogonal frequency division multiplexing with offset quadrature amplitude modulation (OFDM/OQAM) systems is conceived in multipath channels conditions. The cyclic cumulants of OFDM/OQAM signals are derived firstly, symbol timing offset (STO) and carrier frequency offset (CFO) are estimated by employing two groups...
This paper proposes a Doppler estimation algorithm for underwater acoustic communication by constructing the guide function of the objective function based on linear frequency modulation (LFM) signal. The algorithm employs the least square principle and the particle swarm method, to build the objective function and solves the global optimal solution, respectively. Computer simulations show that the...
The under-determined direction of arrival (DOA) estimation problem for a mixture of circular and non-circular signals is studied in the context of sparse arrays and a novel compressive sensing based DOA estimation algorithm is proposed. Compared to a direct application of existing compressive sensing based DOA estimation algorithm, the new one can make a more effective use of the degree of freedoms...
The micro-Doppler (m-D) feature is regarded as a unique characteristic for target recognition. Sparse recovery based approaches for m-D parameter estimation using the single measurement vector (SMV) model have shown their effectiveness recently. However, SMV only fits for narrowband m-D signals, and accurate parameters can hardly be estimated using SMV in strong noise. The signals with the same sparse...
The modeling of fluid catalytic cracking unit (FCCU) is important due to the significant role of FCCU in oil refining. On account of the strong nonlinearity of FCCU mechanisms the solved optimized parameters are usually local optimum, which is sensible to the parameter initial value. A parameter estimation framework and algorithm is proposed in this paper for getting a stable optimal solution. According...
In order to overcome the difficulty of estimating the accurate time delay in the furnace with low and time-varying SNR, the FOC-ETDGE algorithm is studied. The algorithm separates the adaptive processes of SNR and time delay, decomposes the single adaptive filter in the traditional model into the two sub-adaptive units, one of which is used to track the time delay estimate, and the other is used to...
Techniques for dense semantic correspondence have provided limited ability to deal with the geometric variations that commonly exist between semantically similar images. While variations due to scale and rotation have been examined, there is a lack of practical solutions for more complex deformations such as affine transformations because of the tremendous size of the associated solution space. To...
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