Event-triggered cooperative target tracking in wireless sensor networks

Since the issues of low communication bandwidth supply and limited battery capacity are very crucial for wireless sensor networks, this paper focuses on the problem of event-triggered cooperative target tracking based on set-membership information filtering. We study some fundamental properties of the set-membership information filter with multiple sensor measure-ments. First, a sufficient condition is derived for the set-membership information filter, under which the boundedness of the outer ellipsoidal approximation set of the estimation means is guaranteed. Second, the equivalence property between the parallel and sequential versions of the set-membership information filter is presented. Finally, the results are applied to a 1D event-triggered target tracking scenario in which the negative information is exploited in the sense that the measurements that do not satisfy the triggering conditions are modelled as set-membership mea-surements. The tracking performance of the proposed method is validated with extensive Monte Carlo simulations.     

Near real-time PPP-based monitoring of the ionosphere using dual-frequency GPS/BDS/Galileo data

Ionosphere delay is very important to GNSS observations, since it is one of the main error sources which have to be mitigated even eliminated in order to determine reliable and precise positions. The ionosphere is a dispersive medium to radio signal, so the value of the group delay or phase advance of GNSS radio signal depends on the signal frequency. Ground-based GNSS stations have been used for ionosphere monitoring and modeling for a long time. In this paper we will introduce a novel approach suitable for single-receiver operation based on the precise point positioning (PPP) technique. One of the main characteristic is that only carrier-phase observations are used to avoid particular effects of pseudorange observations. The technique consists of introducing ionosphere ambiguity parameters obtained from PPP filter into the geometry-free combination of observations to estimate ionospheric delays. Observational data from stations that are capable of tracking the GPS/BDS/GALILEO from the International GNSS Service (IGS) Multi-GNSS Experiments (MGEX) network are processed. For the purpose of performance validation, ionospheric delays series derived from the novel approach are compared with the global ionospheric map (GIM) from Ionospheric Associate Analysis Centers (IAACs). The results are encouraging and offer potential solutions to the near real-time ionosphere monitoring.     

基于改进GPC的无人直升机动态路径规划

针对小型无人直升机航迹受到风场扰动和导航系统定位误差影响下的航迹最优规划问题,建立了风扰动和导航误差影响下的飞行航迹线性模型。基于混合整数规划思想,采用粒子滤波改进广义模型预测控制算法实时规划航迹,降低了导航定位误差造成的航迹估计偏差,提高了航迹估计精度。仿真结果表明,该算法能够生成三维可行航迹并躲避障碍物,且规划时间和无人机能耗较传统方法显著减少。     

微小型无人直升机姿态信号的互补滤波融合算法

基于惯性测量技术获取飞行器姿态信号的方法已被广泛应用,然而对于微小型或低成本无人飞行器而言,通过MEMS传感器获取满足精度要求且稳定可靠的姿态信号仍然是具有一定难度的工程问题。文章针对民用微小型无人直升机的低成本要求和使用环境,利用三轴角速率陀螺仪和加速度计在姿态估计中频率互补的特性,采用互补滤波算法,改进了滤波参数的自适应调整方法,实现了俯仰角和滚转角信号的有效融合,得到的姿态信息可用于微小型无人直升机的内环增稳控制。仿真和试验数据表明,该方法测量精度较高,工程实现简单,算法稳定,能有效解决微小型无人直升机姿态信号的工程求解和使用问题。     

一种新的SMC-PHD滤波的多目标状态估计方法

针对现有的应用于多目标跟踪概率假设密度粒子滤波器的目标状态估计方法不能很好地解决目标密度较高情况下的多目标状态估计问题,提出了一种新的基于粒子标签的多目标状态估计方法。该方法利用附加在每个粒子上的身份标签将粒子分为不同的粒子群,粒子群的个数与概率假设密度粒子滤波器的目标估计个数相同。随后根据粒子与最近量测的似然函数估计目标的运动状态,使得粒子概率假设密度滤波器在目标密集的情况下仍能准确地估计出目标状态。仿真试验表明,论文所提方法在目标密度较大情况下能够较好地估计出多目标状态,并提高了目标关联的准确性。     

DSP课程实践教学研究

实践教学是DSP教学的重要组成部分。以实例项目导入方式,设计了DSP实践教学内容,给出了相应的系统组成、硬件原理图以及系统的特点。同时从实验室开放和结合科研两个方面,探讨了实践教学方法。对于深化DSP课程实践教学改革有着很好的指导意义。     

Remote sounding of atmospheric gravity waves with satellite limb and nadir techniques

Recent advances in satellite techniques hold great potential for mapping global gravity wave (GW) processes at various altitudes. Poor understanding of small-scale GWs has been a major limitation to numerical climate and weather models for making reliable forecasts. Observations of short-scale features have important implication for validating and improving future high-resolution numerical models. This paper summarizes recent GW observations and sensitivities from several satellite instruments, including MLS, AMSU-A, AIRS, GPS, and CLAES. It is shown in an example that mountain waves with horizontal wavelengths as short as 30 km now can be observed by AIRS, reflecting the superior horizontal resolution in these modern satellite instruments. Our studies show that MLS, AMSU-A and AIRS observations reveal similar GW characteristics, with the observed variances correlated well with background winds. As a complementary technique, limb sounding instruments like CRISTA, CLAES, and GPS can detect GWs with better vertical but poorer horizontal resolutions. To resolve different parts of the broad GW spectrum, both satellite limb and nadir observing techniques are needed, and a better understanding of GW complexities requires joint analyses of these data and dedicated high-resolution model simulations.     

基于卡尔曼滤波器残差的矢量跟踪完好性研究

针对接收机跟踪卫星导航信号时可能发生的各类故障,利用卡尔曼滤波器的残差观测量进行滤波,通常可以在不借助冗余观测量的情况下快速检测和隔离故障。建立软件接收机平台,利用卡尔曼滤波器进行导航信号的矢量跟踪,在跟踪环中模拟故障的发生并依靠残差序列滤波的方法检测并排除错误观测量。实验表明,在算法模拟的短时较大幅度干扰下,完好性监测方法可以快速检测并排除错误观测量对环路跟踪的影响,且无需冗余观测量。     

定频积分控制有源电力滤波器的研究

研究了定频积分控制有源电力滤波器的基本工作原理，并详细分析了它的谐波抑制和无功功率补偿原理。     

基于卡尔曼滤波和主元分析的发动机性能衰退

在给定测量参数基础上,通过非线性估计得到对应离散时刻的部件性能参数,利用数据插值方法扩充测量参数。利用主元分析方法对这些测量参数进行分解,提取反映性能衰退的成分,以此构造反映性能变化的统计量,假定该统计量服从,分布,对性能衰退情况做进一步分析,得到在10000时间点附近性能衰退最为严重,已超过阀值,与前面参数估计结果相符。用部件性能衰退分析方法对发动机性能状况监控,为及时采取维护措施提供了一定的指导作用。