WiFi Indoor Positioning and Tracking Algorithm Based on Compressive Sensing and Sage-Husa Adaptive Kalman Filter

Aiming at the problem that the positioning accuracy of WiFi indoor positioning technology based on location fingerprint has not reached the requirements of practical application, a WiFi indoor positioning and tracking algorithm combining adaptive affine propagation (AAPC), compressed sensing (CS) and Kalman filter is proposed. In the off-line phase, AAPC algorithm is used to generate clustering fingerprints with optimal clustering effect performance;In the online phase, CS and nearest neighbor algorithm are used for position estimation;Finally, the Kalman filter and physical constraints are combined to perform positioning and tracking. By collecting a large number of real experimental data, it is proved that the developed algorithm has higher positioning accuracy and more accurate trajectory tracking effect.

BeiDou B1I/B3I Signals Joint Tracking Algorithm Based on Kalman Filter

Dual-frequency satellite positioning receivers are widely used because they can eliminate ionospheric delay and solve the full-circumference ambiguity quickly.However,in traditional dual-frequency receivers,the relevance of dual-frequency signals are not considered,and,with no improvement imposed to the tracking loop,two independent tracking loops are used to achieve the tracking of dual-frequency signals.In this paper,the Bei Dou dual-frequency signals joint tracking algorithm based on Kalman filter is proposed for the tracking of Bei Dou B1I and B3I dual-frequency signals.Taking the relevance of B1I and B3I signals into consideration,the algorithm adds a Kalman filter between the phase detector and carrier loop filter of the traditional dual-frequency independent tracking loop.The output results of the phase detectors of the B1I and B3I branches are then combined and filtered by the Kalman filter,and the results are input to the carrier loop filters of the corresponding branches.Proved by experiments,the algorithm not only enables the loop to enter a stable tracking state quickly,but also reduces the noise bandwidth of the two loop filters by about 10 Hz with the same tracking performance obtained.

Continuous Tracking of GPS Signals with Data Wipe-Off Method

The decentralized pre-filter based vector tracking loop(VTL)configuration with data wipe-off(DWO)method of the Global Positioning System(GPS)receiver is proposed for performance enhancement.It is a challenging task to continuously track the satellites’signals in weak signal environment for the GPS receiver.VTL is a very attractive technique as it can provide tracking capability in signal-challenged environments.In the VTL,each channel will not form a loop independently.On the contrary,the signals in the channels of VTL are shared with each other;the navigation processor in turn predicts the code phases.Thus,the receiver can successfully track signals even the signal strength from individual satellite is weak.The tracking loop based on the pre-filter provides more flexible adjustment to specific environments to reduce noise interference.Therefore,even if the signals from some satellites are very weak the receiver can track them from the navigation results based on the other satellites.The navigation data,which contains information necessary to perform navigation computations,are binary phase-shift keying(BPSK)modulated onto the GPS carrier phase with the bit duration of 20 ms(i.e.,50 bits per second)for the GPS L1 C/A signals.The coherent integration interval can be extended for improved tracking performance in signal-challenged environment.However,tracking accuracy is decreased by possible data bit sign reversal.The DWO algorithm can be employed to remove the data bit in I and Q correlation values so as to avoid energy loss due to bit transitions when the integration interval of the correlator is extended over 20 ms under the low carrier-to-noise ratio(C/No)environments.The proposed method has an advantage to provide continuous tracking of signals and obtain improved navigation performance.Performance evaluation of the tracking capability as well as positioning accuracy will be presented.

A new tracking error detection method using amplitude difference detection for signal waveform modulation multi-level discs

The sub-land/sub-pit affects the characteristic of the tracking error signal which is generated by the conventional differential phase detection （DPD） method in the signal waveform modulation multi-level （SWML） read-only disc. To solve this problem, this paper proposes a new tracking error detection method using amplitude difference. Based on the diffraction theory, the amplitude difference is proportional to the tracking error and is feasible to be used for obtaining the off-track information. The experimental system of the amplitude difference detection method is developed. The experimental results show that the tracking error signal derived from the new method has better performance in uniformity and signal-to-noise ratio than that derived from the conventional DPD method in the SWML read-only disc.

Dual-assisted high-precision tracking technique for wideband multiplexed signals in new generation GNSS

With the evolution of Global Navigation Satellite System(GNSS),new generation GNSS signals have adopted the dual-frequency multiplexing modulation techniques,which jointly modulate multiple signals located on multiple sub-frequencies into a Wideband Multiplexed Signal(WMS).Although WMSs were proposed initially to reduce the complexity of satellite transmitters and improve the transmission efficiency of signals,their multi-component structures and wide root mean square bandwidths introduced by high-frequency subcarriers also provide the possibility to improve the GNSS ranging precision.Therefore,this paper proposes a Dual-assisted Multi-component Tracking(DMT)technique,which can not only fully use high-frequency subcarriers in WMSs,but also effectively track carrier,subcarrier,and code by jointly utilizing all components in WMS.In this paper,the tracking and ranging performances of DMT are comprehensively analyzed theoretically and by simulation and real experiments.The results show that compared with existing WMS tracking methods,DMT can achieve tracking results with lower tracking jitters and ranging results with higher precision,providing a highly advantageous solution for new generation GNSS signal processing.

Tracking algorithm of BPSK signal in low bit SNR and high dynamic scenarios

A new tracking algorithm is proposed aiming at the tracking problem in low bit signal-to- noise ratio （i. e. , Eb/N0 ） scenarios, in which the bit clock regenerated by bit synchronization loop decides loop update moment. The double frequency processing and non-coherent accumulation tech- nologies are applied to eliminate the impact of data polarity inversion, and then long time accumula- tion improves the input signal-to-noise ratio of discriminator. The frequency locked loop and phase locked loop constitute a carrier loop in parallel, which can meet the high dynamic demands. The ef- fectiveness of this algorithm has been corroborated by theoretical analysis, simulation and measure- ments, and the new tracking algorithm has been used in an aerospace engineering project successfully.

Influence of Design Reference on Tracking Performance of Feedback Control

In this paper, we present an investigation on the tracking performances of feedback control as a function of reference signals. We use multi-objective optimal designs of feedback controls as a fair basis for comparing different control designs, and examine step, ramp, and periodic signals at various frequencies. Through comparing the tracking performances of controls designed with different reference signals,we find that the controls designed with ramp signals perform better in tracking step and ramp references than those designed with step signals. To track periodic signals, we find that the controls designed with periodic signals at the same frequency generally provide the best performance, and those designed with step and ramp signals perform comparably.

Improved MPPT Control Based on the Reduction of Tracking Range

考虑到基于转矩调整的改进方法存在难以获取最优调整状态的问题，该文针对传统功率曲线法提出收缩风机转速的跟踪区间、减小跟踪路程的改进思路，以优化风机最大功率点跟踪的性能。在此基础上，设计出根据平均风速，周期性的调整起始发电转速的改进功率曲线法。其设计机理在于风速平均值恰好反映了风速及风能量集中分布的区间。因此，最优转速跟踪区间与平均风速存在数量上的直接关系而变得容易预估，且无需迭代搜索。与目前基于调整转矩的改进方法相比，该文所提方法不仅提高了风能捕获效率，且简单易行。最后，通过对模拟风速序列的仿真计算与比较分析，验证了该方法的有效性和先进性。

GPS Vector Tracking Loop with Fault Detection and Exclusion

In this paper,both the integrity monitoring and fault detection and exclusion(FDE)mechanisms are incorporated into the vector tracking loop(VTL)architecture of the Global Positioning System(GPS)receiver for reliability enhancement.For the VTL,the tasks of signal tracking and navigation state estimation no longer process separately and a single extended Kalman filter(EKF)is employed to simultaneously track the received signals and estimate the receiver’s position,velocity,etc.In contrast to the scalar tracking loop(STL)which utilizes the independent parallel tracking loop approach,the VTL technique is beneficial from the correlation of each satellite signal and user dynamics.The VTL approach provides several important advantages.One of the merits is that the tracking loop can be assisted for overcoming the problem of signal blockage.Although the VTL architectures provide several important advantages,they suffer some fundamental drawbacks.For example,the errors in the navigation solutions may degrade the tracking accuracy.The most significant drawback is that failure of tracking in one channel may affect the entire tracking loop and possibly lead to loss of lock.For reliability enhancement,the EKF based integrity monitoring and FDE algorithms are developed to prevent the error from spreading into the entire tracking loop.The integrity monitoring is utilized to check the possible fault in the pseudorange and the pseudorange rate,followed by the FDE mechanism employed to exclude the abnormal satellite signals.Performance assessment and evaluation for the proposed approach will be presented.

Sensor Scheduling Algorithm Target Tracking-Oriented

Target tracking is a challenging problem for wireless sensor networks because sensor nodes carry limited power recourses. Thus, scheduling of sensor nodes must focus on power conservation. It is possible to extend the lifetime of a network by dynamic clustering and duty cycling. Sensor Scheduling Algorithm Target Tracking-oriented is proposed in this paper. When the target occurs in the sensing filed, cluster and duty cycling algorithm is executed to scheduling sensor node to perform taking task. With the target moving, only one cluster is active, the other is in sleep state, which is efficient for conserving sensor nodes’ limited power. Using dynamic cluster and duty cycling technology can allocate efficiently sensor nodes’ limited energy and perform tasks coordinately.

Adaptively Robust Phase Lock Loop for Low C/N Carrier Tracking in a GPS Software Receiver

在 GPS 应用程序的一个重要问题是怎么追踪 GPS (全球放系统) 在低 carrier-to-noise 比率(C/N ) 下面精确并且连续地发信号。在这份报纸，一个适应地柔韧的过滤器基于低 C/N 搬运人阶段锁循环(PLL ) 在一个 GPS 软件接收装置平台下面被开发。就传统的追踪循环上的低 C/N 搬运人信号的效果而言，追踪循环的平行关联被建立。一个线性最佳的评估者被设计在 kinematics 模型和大小处理依赖噪音。而且，一个适应地柔韧的过滤器基于三片断功能被设计调整因素。当收到的信号在有利条件下面时，新过滤器的表演很类似于一个标准 Kalman 过滤器。为追踪的一个实际弱搬运人，这新提高的 PLL 聪明地根据全部的阶段神经质分析调节循环参数。它成功地由适应地平衡更新的动态模型状态和大小的影响抵抗孤立点和动态模型错误。新过滤器的坚韧性和效率被测试实验的一些真实数据表明。结果证实有追踪循环的这个适应地柔韧的阶段的阶段错误的标准差能在 24 dB-Hz 附近与卫星 C/N 比率到达 0.01 个周期，它显著地改进表演。

Influence of B1 code correlation loop for vector tracking structures under complicated environment

The code tracking loop is a key component for user positioning. The pseudorange information of Bei Dou B1 signals has been fused and changed for vector tracking, so a correlation output model for complex scenarios is designed to prevent the propagation of error and valuate the signal performance. The relevant software and hardware factors that affect the output are analyzed.A single channel time-division multiplexing(TDM) method for multicorrelation data extraction is proposed. Statistical characteristics of the correlation output data for both vector and scalar structures are evaluated. Simulation results show that correlation outputs for both structures follow normal or Chi-squared distributions in normal conditions, and the Gamma distribution in harsh conditions. It is shown that a tracking model based on the multi-channel fusion hardly changes the probability distribution of the correlation output in the normal case, but it reduces the ranging error of the code loop, and hence the tracking ability of the code loop for weak signals is improved. Furthermore, vector tracking changes the pseudorange characteristics of channels anytime, and affects the mutual correlation outputs of the code loops in the abnormal case. This study provides a basis for the subsequent design of autonomous integrity algorithms for vector tracking.

Application of Heterogeneous Multiple Feature Data Fusion to Multitarget Association and Tracking

In this paper we discuss a kind of multitarget tracking and association method based on the data fusion of heterogeneous multiple feature data gained by a sensor such as space state, signal amplitude, Doppler frequency and so on. In order to introduce quantitatively those heterogeneous multiple feature data which are possibly gained by a sensor into the discussion of tracking and association problem, we define a correlation measure which we explain as the generalization of conventional association decision. In conventional Nearest Neighbor method, the decision function can take only two values, 1 or 0, to represent the decision of association or not association. In our method, correlation measure can be take any real value from 0 to 1 to represent the extent of correlation. Considering the practical circumstances that some feature data might not be easily gained continuously, we introduce an effective factor to deal with these cases. In the paper we also discuss the comparative computer simulation tests and give the results.

Gaussian Convolution Filter and its Application to Tracking

A new recursive algorithm, called the Gaussian convolution filter (GCF), is proposed for nonlinear dynamic state space models. Based on the convolution filter (CF) and similar to the Gaussian filters, the GCF ap-proximates the posterior density of the states by Gaussian distribution. The analytical results show the ability to deal with complex observation model and small observation noise of the GCF over the Gaussian particle filter (GPF) and the lower complexity, more amenable for parallel implementation than the CF. The Simula-tion in the Tracking domain demonstrates the good performance of the GCF.

A De-Noising Method for Track State Detection Signal Based on EMD

In the track irregularity detection, the acceleration signals of the inertial measurement unit (IMU) output which with low frequency components and noise, this paper studied a de-noising algorithm. Based on the criterion of consecutive mean square error, a de-noising method for IMU acceleration signals based on empirical mode decomposition (EMD) was proposed. This method can divide the intrinsic mode functions (IMFs) derived from EMD into signal dominant modes and noise dominant modes, then the modes reflecting the important structures of a signal were combined together to form partially reconstructed de-noised signal. Simulations were conducted for simulated signals and a real IMU acceleration signals using this method. Experimental results indicate that this method can efficiently and adaptively remove noise, and this method can better meet the precision requirement.

A Survey on Joint Target Tracking and Classification

The JTC technology deals with the problem of target tracking and target classification simultaneously within a unified framework.The fundamental idea of the JTC technology is that by taking advantage of the mutual exchange of useful information between the tracker and classifier,significant improvements in performance of both target tracking and target classification can be expected.The principle of JTC technology is introduced.The existing JTC technologies are broadly categorized into two classes,i.e.,point-target-motion-model-based JTC and rigid-target-motion-based JTC,which are then compared in detail.The advance of the JTC technology is surveyed with comments on some related literatures.Finally,some opening topics of the JTC technology are discussed.

基于多模态数据的在线学习认知负荷评估

近年来,认知负荷过载成为影响在线学习效果的一个重要因素。为解决此问题,文章聚焦在线学习认知负荷评估,首先设计了基于多模态数据的在线学习认知负荷评估研究框架,包含多模态数据采集、多模态特征提取和评估模型构建三个部分。接着,文章通过实验,采集学习者在特定在线学习环境下的多模态数据,提取人脸表情特征、眼动追踪指标特征和脑电信号特征,构建在线学习认知负荷评估模型。之后,文章对评估模型的准确性进行验证,发现在五种机器学习算法模型中,KNN模型的综合性能最佳,故将此模型作为最终的在线学习认知评估模型;同时,文章对多模态数据进行了分析,发现多模态融合方法在认知负荷评估上具有优越性。文章构建的评估模型可赋能在线学习平台实现认知负荷的实时评估,进而实现基于认知负荷的个性化学习,增强学习动机,提升学习效果,促进在线教育质量提升。

基于Duffing振子的铁路轨道移频信号测量系统设计

铁路轨道作为移频信号的传输载体,其对于信号对象传输轨迹疏密度的辨别能力,决定了轨道体系对移频信号的测量准确性;为实现对信号对象传输频率的准确辨别,设计基于Duffing振子的铁路轨道移频信号测量系统;将电源模块输出的电量信号,按需分配至STM32F103微处理器、移频信号辨别模块与DSP测量单元之中,完善各级应用部件之间的连接关系,实现铁路轨道移频信号测量系统的硬件方案设计;确定移频信号的Duffing振子描述条件,针对其定义形式,构造移频信号的相空间,完成对铁路轨道移频信号的提取;求解铁路轨道的Lyapunov指数,并构建移频信号的Duffing方程,确定混沌测量参数的取值范围,实现对铁路轨道移频信号的测量,联合各级应用部件,完成基于Duffing振子的铁路轨道移频信号测量系统设计;实验结果表明,上述系统测量所得信号传输轨迹疏密度与真实轨迹疏密度相似度较高,并且测量结果准确率最高值达到了84%左右,说明其能够实现对铁路轨道移频信号的准确测量。