Study on the estimation of Euler angles for Macao Science Satellite-1

The Euler angle estimation is a calibration method for vector data measured by the magnetometer on a satellite.It is used to find the relative rotation between the coordinate system of the magnetometer and the satellite(usually determined by Star Imagers).Before launch of the low-orbit,low-inclination Macao Science Satellite-1(known as MSS-1),we simulated the estimation of Euler angles by using the magnetic measurements of the in-orbit Swarm and China Seismo-Electromagnetic Satellite(noted as CSES),with various data combinations.In this study,11 data sets were designed to analyze the estimation results for the MSS-1 orbit by using a joint estimation method of the geomagnetic field model parameters and Euler angles.For the model results,we found that all the spatial power spectral lines showed behavior consistent with that of the CHAOS-7.8 model at low degrees(corresponding to large-scale magnetic signals).The spectra of models without global data coverage deviated much more(by a maximum of~10^(4) nT^(2))from those of the CHAOS-7.8 model at higher degrees.For models with global data coverage and with various data combinations,the spectral lines were distributed similarly.Moreover,the models with accordant power spectral distributions demonstrated different Euler angle estimations.As more vector data at higher latitudes were included,the estimated Euler angles varied monotonically in all three directions.The models with vector data in the same latitude range showed similar Euler angle results,regardless of whether the poleward scalar data were included.The largest value difference was found between the models using vector data within±40°latitudes and those using vector data within±60°latitudes,which reached to~28″.Therefore,we concluded that the inversion of the spherical harmonic Gauss coefficients in our tests was mainly affected by the spatial coverage range of the data,whereas the estimation of Euler angles largely depended on the latitude range where the vector data could be obtained.These results can be used for future in-flight data testing.We expect the estimation of Euler angles to improve as other methods are adopted.

Online asymmetry estimation for whole angle mode coriolis vibratory gyroscopes by high frequency injection

The whole angle mode gyroscope(WAMG)is considered to be the next generation architecture,but it is suffered from the asymmetry errors to conduct real products.This paper proposes a novel high frequency injection based approach for the error parameters online identification for the WAMG.The significance is that it can separate physical and error fingerprints to enable online calibration.The nonlinear WAMG dynamics are discretized to meet the requirement of numerical precision and computation efficiency.The optimized estimation methods are then constructed and compared to track asymmetry error parameters continuously.In the validation part,its results firstly prove that the proposed scheme can accurately identify constant asymmetry parameters with an overall tracking error of less than 1 ppm and the extreme numerical convergence can reach 10^(-12)ppm.Under the dynamic asymmetry variation condition,the root mean square errors(RMSE)indicate that the tracking accuracy can reach the level of10^(-3),which shows the robustness of the proposed scheme.In summary,the proposed method can effectively estimate the WAMG asymmetry errors online with satisfied performance and practical values.

Angle estimation in bistatic MIMO radar using improved reduced dimension Capon algorithm

This paper discusses the problem of direction of departure （DOD） and direction of arrival （DOA） estimation for a bistatic multiple input multiple output （MIMO） radar, and proposes an improved reduced-dimension Capon algorithm therein. Compared with the reduced-dimension Capon algorithm which requires pair matching between the two-dimensional angle estimation, the pro- posed algorithm can obtain automatically paired DOD and DOA estimation without debasing the performance of angle estimation in bistatic MIMO radar. Furthermore, the proposed algorithm has a lower complexity than the reduced-dimension Capon algorithm, and it is suitable for non-uniform linear arrays. The complexity of the proposed algorithm is analyzed and the Cramer-Rao bound （CRB） is also derived. Simulation results verify the usefulness of the proposed algorithm.

Elevation estimation for low-angle target based on reffection paths suppression

In the signal processing for metrewave radar, the reflection paths of target echoes can cause severe error in the elevation estimation for the low-angle target tracking. The exact angles of the reflection paths are unknown beforehand, and therefore, the reflection paths can not be suppressed easily. Therefore, in this article, an improved reflection paths suppression approach is presented. A block matrix aggregate is constructed based on the possible angles of the reflection paths. Combined with the beamforming-like processing, a generalized maximum likelihood estimation is derived to optimize the estimation. Moreover, the noise reduction method based on the Toeplitz covariance matrix is used for better performance. This approach is applied to the real data collected by the low-angle tracking radar with 8-channel vertical array. The experiment results show that the reflection effects are reduced and the accuracy of the elevation estimate is improved.

Refractivity estimations from an angle-of-arrival spectrum

This paper addresses the probability of atmospheric refractivity estimation by using field measurements at an array of radio receivers in terms of angle-of-arrival spectrum. Angle-of-arrival spectrum information is simulated by the ray optics model and refractivity is expressed in the presence of an ideal tri-linear profile. The estimation of the refractivity is organized as an optimization problem and a genetic Mgorithm is used to search for the optimal solution from various trial refractivity profiles. Theoretical analysis demonstrates the feasibility of this method to retrieve the refractivity parameters. Simulation results indicate that this approach has a fair anti-noise ability and its accuracy performance is mainly dependent on the antenna aperture size and its positions.

Real-domain GMUSIC algorithm based on unitary-transform for low-angle estimation

In order to realize the elevation angle estimation for low-altitude targets at a low computational cost, a generalized multiple signal classification （GMUSIC） algorithm based on unitary transform is proposed, i.e., the DU-GMUSlC algorithm. Firstly, the covariance matrix of received data is used to construct the Centro- Hermitian matrix. Then, the real-domain GMUSIC algorithm is used to implement the initial angle estimation, and the multipath attenuation coefficient is calculated in succession. Finally, the attenuation coefficient is taken into account in the GMUSIC method to carry out the secondary angle estimation which is beneficial to further improvement of the angle estimation accuracy. This method can meet requirements of low-angle accuracy as well as lower computational burden. Simulation results prove the correctness and effectiveness of the proposed algorithm. Moreover, field experiment data are used to further validate the effectiveness of this method.

Beamforming and Angle-of-Arrival Estimation of Square Planar Antenna Array

This paper presents a dual-band planar antenna array for ISM band applications (2.4 GHz and 2.45 GHz). This antenna is proposed for indoor applications and enables adaptive beamforming and angle of arrival (AOA) estimation. An adaptive beamforming algorithm is applied for a planar antenna array, which is able to steer its main beam and nulls in azimuth and elevation planes over a wide frequency band. Planar antenna array operates as a spatial filter in 3D space, processing the received signals with weighting schemes. A planar antenna array is designed for AOA estimation in azimuth and elevation planes by using MUltiple SIgnal Classification (MUSIC) based on subspace algorithm. The Base Station (BS) equipped with this planar antenna is preferred to be at the center position on the room ceiling to cover all sectors of the room. It is designed to use four directional triangular elements arranged to form a square planar antenna array. Planar antenna with four elliptical slotted triangular elements (PAFESTE) is used to obtain optimal directivity in four directions in azimuth plane with specific orientation of 30? in elevation plane. It is characterized by half power beamwidth in elevation plane of about 60? and half power beamwidth in azimuth plane of about 90?.

THE ANGLE ERROR ESTIMATE METHOD IN THE WIDE SWATH SAR BASING ON MULTI-RECEIVER

The wide-swath method based on multi-receiver is a novel and highly accurate wide-swath method, which requires a very precise view angle. The estimated angle has error because of the atmosphere refraction, angle error of view and target height. A method is proposed in this paper to estimate the angle error from the return signal. The method makes use of the relationship between the view angle error and the signal correlation of the subswaths to estimate the angle error. The precision of this method is analyzed by the law of great number and it turns out to be in direct proportion to the root square number of averaging. The simulation result is given and the angle precision is 0.025°.

Vehicle Dynamic State Estimation： State of the Art Schemes and Perspectives

Next-generation vehicle control and future autonomous driving require further advances in vehicle dynamic state estimation. This article provides a concise review, along with the perspectives, of the recent developments in the estimation of vehicle dynamic states. The definitions used in vehicle dynamic state estimation are first introduced, and alternative estimation structures are presented. Then, the sensor configuration schemes used to estimate vehicle velocity, sideslip angle, yaw rate and roll angle are presented. The vehicle models used for vehicle dynamic state estimation are further summarized, and representative estimation approaches are discussed. Future concerns and perspectives for vehicle dynamic state estimation are also discussed.

Fast multi-parameter estimation and localization for MIMO radar

This paper addresses the problem of four-dimensional angle and Doppler frequency estimation for bistatic multiple-input multiple-output （MIMO） radar with arbitrary arrays in spatial co- lored noise. A novel method for joint estimation of Doppler fre- quency, two-dimensional （2D） direction of departure and 2D direc- tion of arrival based on the propagator method （PM） for arbitrary arrays is discussed. A special matrix is constructed to eliminate the influence of spatial colored noise. The four-dimensional （4D） angle and Doppler frequency are extracted from the matrix and the three- dimensional （3D） coordinates of the targets are then calculated on the basis of these angles. The proposed algorithm provides a lower computational complexity and has a parameter estimation very close to that of the ESPRIT algorithm and the DOA-matrix al- gorithm in the high signal to noise ratio and the Cramer-Rao bound （CRB） is given. Furthermore, multi-dimensional parameters can be automatically paired by this algorithm to avoid performance degra- dation resulting from wrong pairing. Simulation results demonstrate the effectiveness of the proposed method.

Frequency domain polarization weighted ESPRIT method for bearing angle

The signal to noise ratio （SNR） of seismic waves is usually very low after long distance transmission. For this condition, to improve the bearing estimation capability in the low SNR, a frequency domain polarization weighted ESPRIT method using a single vector device is proposed. The frequency domain polari- zation parameters extracted from the signals are used to design the weighted function which is applied to the received signals. The bearing angle and the target frequency are estimated through ESPRIT using the weighted signals. The simulation and experiment results show that the presented method can obtain accurate estimation values under the low SNR with little prior information.

Computationally Efficient MUSIC-Based Algorithm for Joint Direction of Arrival (DOA) and Doppler Frequency Estimation in Monostatic MIMO Radar

The problem of joint direction of arrival (DOA) and Doppler frequency estimation in monostatic multiple-input multiple-output (MIMO) radar is studied and a computationally efficient multiple signal classification (CE-MUSIC) algorithm is proposed.Conventional MUSIC algorithm for joint DOA and Doppler frequency estimation requires a large computational cost due to the two dimensional (2D) spectral peak searching.Aiming at this shortcoming,the proposed CE-MUSIC algorithm firstly uses a reduced-dimension transformation to reduce the subspace dimension and then obtains the estimates of DOA and Doppler frequency with only one-dimensional (1D) search.The proposed CE-MUSIC algorithm has much lower computational complexity and very close estimation performance when compared to conventional 2D-MUSIC algorithm.Furthermore,it outperforms estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm.Meanwhile,the mean squared error (MSE) and Cramer-Rao bound (CRB) of joint DOA and Doppler frequency estimation are derived.Detailed simulation results illustrate the validity and improvement of the proposed algorithm.

Target Localization Based on Angle of Arrivals

Mobile location using angle of arrival （AOA） measurements has received considerable attention. This paper presents an approximation of maximum likelihood estimator （MLE） for localizing a source based on AOA measurements. By introducing an intermediate variable, the nonlinear equations relating AOA estimates can be transformed into a set of equations which are linear in the unknown parameters. It is an approximate realization of the MLE. Simulations show that the proposed algorithm outperforms the previous contribution.

A target group tracking algorithm for wireless sensor networks using azimuthal angle of arrival information

In this paper, we explore the technology of tracking a group of targets with correlated motions in a wireless sensor network. Since a group of targets moves collectively and is restricted within a limited region, it is not worth consuming scarce resources of sensors in computing the trajectory of each single target. Hence, in this paper, the problem is modeled as tracking a geographical continuous region covered by all targets. A tracking algorithm is proposed to estimate the region covered by the target group in each sampling period. Based on the locations of sensors and the azimuthal angle of arrival （AOA） information, the estimated region covering all the group members is obtained. Algorithm analysis provides the fundamental limits to the accuracy of localizing a target group. Simulation results show that the proposed algorithm is superior to the existing hull algorithm due to the reduction in estimation error, which is between 10% and 40% of the hull algorithm, with a similar density of sensors. And when the density of sensors increases, the localization accuracy of the proposed algorithm improves dramatically.

STUDY ON MONOPULSE ANGLE MEASUREMENT METHOD BASED ON VIRTUAL POLARIZATION MATCHING

A monopulse angle measurement method for polarization array radar is studied in this paper.The receiving signal model is established and then a monopulse angle measurement method based on virtual polarization matching is proposed.To analyze the estimation performance,the Cramer-Rao Lower Bound(CRLB)of angle estimation is derived.Both theoretical analysis and simulation show that:firstly,the proposed method is superior to the traditional angle measurement methods based on the single polarization.Secondly,the performance of the new method is unrelated to the echo polarization.Thirdly,angle estimation of this method is asymptotically optimal.The results show that this method has great potential to be used in polarization array radar.

Accurate Angle-of-Arrival Measurement Using Particle Swarm Optimization

As one of the major methods for location positioning, angle-of-arrival (AOA) estimation is a significant technology in radar, sonar, radio astronomy, and mobile communications. AOA measurements can be exploited to locate mobile units, enhance communication efficiency and network capacity, and support location-aided routing, dynamic network management, and many location-based services. In this paper, we propose an algorithm for AOA estimation in colored noise fields and harsh application scenarios. By modeling the unknown noise covariance as a linear combination of known weighting matrices, a maximum likelihood (ML) criterion is established, and a particle swarm optimization (PSO) paradigm is designed to optimize the cost function. Simulation results demonstrate that the paired estimator PSO-ML significantly outperforms other popular techniques and produces superior AOA estimates.

空域色噪声下的多输入多输出雷达角度估计

由于多输入多输出(multiple input multiple output,MIMO)雷达的空域色噪声协方差矩阵通常为非对角矩阵,因此在色噪声下信号子空间与噪声子空间无法有效分离,从而致使传统算法无法有效估计目标角度。为此,首先利用信号协方差矩阵的低秩性和色噪声协方差矩阵的稀疏性来抑制空域色噪声。然后,根据MIMO雷达数据的内在多维结构特性,建立四阶张量CP(canonical or parallel factor analysis,CANDECOMP/PARAFAC)分解模型。针对传统交替最小二乘算法对数值病态性较为敏感而导致CP分解精度低的问题,利用张量因子矩阵之间的共轭关系来降低求解的病态敏感度,提高张量分解的稳健性。最后,利用最小二乘拟合法从因子矩阵的估计值中得到目标角度。仿真结果表明,所提算法能够对色噪声有效抑制并提高了角度估计的精度。

基于GA-BP神经网络的大型客机气流角估计方法

为了解决硬件冗余难以克服的气流角传感器共因故障问题,进一步提高飞机气流角信号的可靠性,研究了基于GABP神经网络的气流角估计方法。通过BP神经网络融合姿态角、加速度、风速等参数来实现不依赖气流角传感器的气流角估计;引入遗传算法对神经网络权值和阈值进行全局优化,提高估计精度;对某大型客机的试飞数据预处理后用于模型的训练和测试。仿真结果表明,训练完成的GA-BP神经网络模型对气流角的估计值贴近实际值,稳定性和精度明显高于BP神经网络。上述方法给飞机增加一个余度的气流角信号,可用于传感器故障时为飞机提供可靠的气流角信号。

霍尔效应实验自主分层次教学探究

为了解决2023版《理工科类大学物理实验课程教学基本要求》中分层次教学要求与现有仪器设备不完全匹配问题,我们结合本校实际探索了一条低投入高效能的自主化分层次实验教学途径。本文以霍尔效应实验自主化分层次教学实践为例,探究了如何在现有B层次的实验仪器上,细挖深究结合动手改造,开展C层次研究性实验和D层次设计性实验。在霍尔效应副效应研究性实验中,我们评估了所有效应的阶数,并定量测量了副效应引起的附加电势差;在角度传感器设计性实验中,我们完成了基于霍尔效应的角度传感器设计,并发展了一套两参量最小二乘法误差处理方法。自主化分层次实验教学有助于因地制宜地开展实验教学改革,提升实验教学质量。

自适应双层无迹卡尔曼滤波的车辆状态估计

针对在车辆行驶状态估计中存在估计不准确、鲁棒性较差以及系统噪声不确定等问题,提出一种将双层无迹卡尔曼滤波(DLUKF)与改进的Sage-Husa算法相结合的自适应双层无迹卡尔曼滤波算法(ADLUKF)作为车辆行驶状态的估计器,再结合三自由度汽车模型对车辆行驶的横摆角速度和质心侧偏角进行估计。通过改进的Sage-Husa滤波器对系统过程噪声和测量噪声进行动态调整,进而减少车辆行驶状态估计的误差。应用Carsim与Matlab/Simulink进行联合仿真以及实车试验数据来验证该估计器的有效性,并与无迹卡尔曼滤波(UKF)算法进行对比。结果表明:与UKF算法相比,该算法有效提高了车辆行驶的横摆角速度和质心侧偏角的估计精度和稳定性。