A ScanSAR Roll Angle Iterative Estimation Algorithm Based on Least Square Method

2011 ◽  
Vol 30 (9) ◽  
pp. 2099-2102
Author(s):  
Xin Li ◽  
Jun Hong
Keyword(s):  
Least Square Method ◽  
Estimation Algorithm ◽  
Least Square ◽  
Roll Angle ◽  
Iterative Estimation

scholarly journals Research on error compensation in the process of geomagnetic sensor measurement

2021 ◽  
Vol 17 (5) ◽  
pp. 155014772110199
Author(s):  
Zhang Pingan ◽  
Wang Wei ◽  
Gao Ming ◽  
Wang Yi
Keyword(s):  
Error Compensation ◽  
Least Square Method ◽  
Angle Measurement ◽  
Least Square ◽  
Roll Angle ◽  
Error Sources ◽  
Compensation Model ◽  
Highly Sensitive ◽  
Sensitive Sensor ◽  
Fitting Model

The geomagnetic sensor is a kind of highly sensitive sensor, which is easy to be interfered with by the outside in the process of measurement. To solve this problem, the author uses the least square method to estimate the gain value and sensitivity product value of the amplification circuit of the geomagnetic sensor and explores the solution of the bias voltage of the geomagnetic sensor by using the ellipsoid fitting model. By analyzing the error sources of the geomagnetic sensors in the measurement process, the error compensation model covering various error factors is constructed. All parameters of the error compensation model are obtained by fitting the experimental data of the turntable. After several experiments with different attitude angles, the validity of the compensation model is verified, and the measurement accuracy of the roll angle is improved, which meets the requirements of roll angle measurement.

A mass and road slope integrated estimation strategy based on the joint iteration of least square method and Sage-Husa adaptive filter for autonomous logistics vehicle

2021 ◽  
pp. 095440702110417
Author(s):  
Weida Wang ◽  
Yuanbo Zhang ◽  
Ke Chen ◽  
Hua Zhang ◽  
Xiantao Wang ◽  
...  
Keyword(s):  
Adaptive Filter ◽  
Autonomous Vehicles ◽  
Least Square Method ◽  
Estimation Algorithm ◽  
Least Square ◽  
Recursive Least Square ◽  
Estimation Strategy ◽  
Vehicle Mass ◽  
Integrated Estimation ◽  
Road Slope

Autonomous logistics vehicles are characterised by large changes in mass and their performances are greatly influenced by slope. In addition, sensors on autonomous vehicles are expensive and difficult to be installed considering application environment. To address these problems, a novel integrated estimation strategy for vehicle mass and road slope, which is based on the joint iteration of multi-model recursive least square (MMRLS) and Sage-Husa adaptive filter with the strong tracking filter (SH-STF), is proposed by utilising information involving speed, nominal engine torque and inherent parameters of vehicles. Firstly, due to the separate slowly-changing and time-dependent characteristics, the vehicle mass and road slope are estimated by using MMRLS and SH-STF separately. Secondly, the longitudinal dynamics gain and the steering dynamics gain are calculated separately based on each model’s residual probability distribution. Then, the two estimations module are combined by employing an iterative algorithm. Finally, the proposed strategy is verified by simulation and real vehicle tests. The tests result reveals that the estimation algorithm can effective estimate vehicle mass and road slope in real-time under straight going and steering conditions.

scholarly journals A Demand Estimation Algorithm for Inventory Management Systems Using Censored Data

2017 ◽  
Vol 7 (6) ◽  
pp. 2215-2221
Author(s):  
A. Nikseresht ◽  
K. Ziarati
Keyword(s):  
Inventory Management ◽  
Censored Data ◽  
Choice Model ◽  
Product Category ◽  
Least Square Method ◽  
Estimation Algorithm ◽  
Least Square ◽  
Model Parameters ◽  
Demand Model ◽  
Customer Choice

During the selling time horizon of a product category, a number of products may become unavailable sooner than others and the customers may substitute their desired product with another or leave the system without purchase. So, the recorded sales do not show the actual demand of each product. In this paper, a nonparametric algorithm to estimate true demand using censored data is proposed. A customer choice model is employed to model the demand and then a nonlinear least square method is used to estimate the demand model parameters without assuming any distribution on customer’s arrival. A simple heuristic approach is applied to make the objective function convex, making the algorithm perform much faster and guaranteeing the convergence. Simulated dataset of different sizes are used to evaluate the proposed method. The results show a 23% improvement in root mean square error between estimated and simulated true demand, in contrast to alternate methods usually used in practice.

Research on the Parameter Estimating Algorithms of Image Edge Detection

2012 ◽  
Vol 562-564 ◽  
pp. 1279-1285
Author(s):  
Ya Ceng Shang ◽  
Jing Chen ◽  
Jun Wei Tian
Keyword(s):  
Linear Model ◽  
Likelihood Estimation ◽  
Least Square Method ◽  
Estimation Algorithm ◽  
Least Square ◽  
Great Likelihood ◽  
Index Model ◽  
Non Linear ◽  
Image Edge ◽  
Future Choice

During detecting the edge of the images, the text partly use great likelihood estimation and least square method estimation algorithm to estimate, we found the result of two estimate algorithms used in the same model are different through experimental analysis. Aiming at above mentioned problems, this text divides the commonly used model in pattern process into the linear model and non-linear model, among the non-linear model, it divides into multinomial model, gauss model, shouldered index model and power counting model, and this text use great likelihood estimate algorithm and least square method estimation algorithm to estimate these models separately, and draw their scope of the application through the experiment, also provide the convenience for the future choice.

Pose Estimation of Cooperative Targets for Space Exploration Task Based on Binocular Visual Measurement

2013 ◽  
Vol 333-335 ◽  
pp. 268-274
Author(s):  
Jing Jing Wang ◽  
Jian Yu Huang ◽  
Shi Yin Qin
Keyword(s):  
Pose Estimation ◽  
Three Dimensional ◽  
Least Square Method ◽  
Estimation Algorithm ◽  
High Accuracy ◽  
Least Square ◽  
Estimation Accuracy ◽  
Feature Points ◽  
Well Performance ◽  
Visual Measurement

In this paper, a high accuracy and efficiency pose estimation algorithm is proposed for space cooperative targets in RVD based on binocular visual measurement. At first, the scheme of visual measurement toward RVD is presented and the environment conditions and performance requirement are analysed and discussed. Then the relationship of pose estimation with detection and tracking is studied to give an implementing strategy of pose estimation with high accuracy and efficiency. Moreover, the key point is focused on the pose estimation of cooperative targets, in which a stereo vision mapping relation between three dimensionl coordinates of spacial feature points of cooperative targets and their corresponding image coordinates is established, then the least square method is employed to estimate the three-dimensional coordinates of feature points so as to calculate the relative position and attitude between tracking spacecraft and target spacecraft with high precision, finally a series of experimental resluts indicate that the proposed pose estimation algorithm under binocular visual measurement demonstrates well performance in the estimation accuracy, anti-noise and real-time thus can achieve the application requriements of RVD under binocular visual measurement.

scholarly journals Generalized Sparse Polarization Array for DOA Estimation Using Compressive Measurements

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Tao Chen ◽  
Jian Yang ◽  
Weitong Wang ◽  
Muran Guo
Keyword(s):  
Degrees Of Freedom ◽  
Elevation Angle ◽  
Least Square Method ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Least Square ◽  
Polarization Angle ◽  
Estimation Performance ◽  
The Difference ◽  
Cramer Rao Bound

The compressive array method, where a compression matrix is designed to reduce the dimension of the received signal vector, is an effective solution to obtain high estimation performance with low system complexity. While sparse arrays are often used to obtain higher degrees of freedom (DOFs), in this paper, an orthogonal dipole sparse array structure exploiting compressive measurements is proposed to estimate the direction of arrival (DOA) and polarization signal parameters jointly. Based on the proposed structure, we also propose an estimation algorithm using the compressed sensing (CS) method, where the DOAs are accurately estimated by the CS algorithm and the polarization parameters are obtained via the least-square method exploiting the previously estimated DOAs. Furthermore, the performance of the estimation of DOA and polarization parameters is explicitly discussed through the Cramér-Rao bound (CRB). The CRB expression for elevation angle and auxiliary polarization angle is derived to reveal the limit of estimation performance mathematically. The difference between the results given in this paper and the CRB results of other polarized reception structures is mainly due to the use of the compression matrix. Simulation results verify that, compared with the uncompressed structure, the proposed structure can achieve higher estimated performance with a given number of channels.

Direct Assessment of Effective Renal Plasma Flow from Renoscintigraphy with a Gamma Camera and an On-Line Computer

1981 ◽  
Vol 20 (06) ◽  
pp. 274-278
Author(s):  
J. Liniecki ◽  
J. Bialobrzeski ◽  
Ewa Mlodkowska ◽  
M. J. Surma
Keyword(s):  
Count Rate ◽  
Renal Plasma Flow ◽  
Early Period ◽  
Least Square Method ◽  
Least Square ◽  
Uptake Coefficient ◽  
Positive Linear Correlation ◽  
On Line ◽  
Best Fit ◽  
Plasma Activity

A concept of a kidney uptake coefficient (UC) of 131I-o-hippurate was developed by analogy from the corresponding kidney clearance of blood plasma in the early period after injection of the hippurate. The UC for each kidney was defined as the count-rate over its ROI at a time shorter than the peak in the renoscintigraphic curve divided by the integral of the count-rate curve over the "blood"-ROI. A procedure for normalization of both curves against each other was also developed. The total kidney clearance of the hippurate was determined from the function of plasma activity concentration vs. time after a single injection; the determinations were made at 5, 10, 15, 20, 30, 45, 60, 75 and 90 min after intravenous administration of 131I-o-hippurate and the best-fit curve was obtained by means of the least-square method. When the UC was related to the absolute value of the clearance a positive linear correlation was found (r = 0.922, ρ > 0.99). Using this regression equation the clearance could be estimated in reverse from the uptake coefficient calculated solely on the basis of the renoscintigraphic curves without blood sampling. The errors of the estimate are compatible with the requirement of a fast appraisal of renal function for purposes of clinical diagknosis.

PENGARUH KNOWLEDGE MANAGEMENT, KOMPETENSI, MOTIVASI TERHADAP KINERJA KARYAWAN

2015 ◽  
Vol 5 (2) ◽  
pp. 1
Author(s):  
Miftahol Arifin
Keyword(s):  
Knowledge Management ◽  
Linear Regression ◽  
Significant Influence ◽  
Employee Performance ◽  
Least Square Method ◽  
Least Square ◽  
Analysis Tool ◽  
Ordinary Least Square ◽  
Competence Motivation ◽  
Performance Analyze

The purpose of this research is to analyze the influence of knowledge management on employee performance, analyze the effect of competence on employee performance, analyze the influence of motivation on employee performance). In this study, samples taken are structural employees PT.centris Kingdom Taxi Yogyakarta. The analysis tool in this study using multiple linear regression with Ordinary Least Square method (OLS). The conclusion of this study showed that the variables of knowledge management has a significant influence on employee performance, competence variables have an influence on employee performance, motivation variables have an influence on employee performance, The analysis showed that the variables of knowledge management, competence, motivation on employee performance.Keywords: knowledge management, competence, motivation, employee performance.

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