A FastSLAM Algorithm Based on the Improved Auxiliary Particle Filter with Stirling Interpolation

The choice of the particle's distribution model and the consistency of the result are very important for FastSLAM.The improved auxiliary variable model with FastSLAM,and Stirling Interpolation which is used to approximate the nonlinear functions are provided.This approach improves the precision of the approximation for the nonlinear functions,conquers the drawback of the FastSLAM1.0 by using a model ignoring the measurement data,enhances the estimation consistency of the robot pose,and reduces the degradation speed of the particle in FastSLAM algorithm.Simulation results demonstrate the excellence of the proposed algorithm and give the noise parameter influence on the proposed algorithm.

A semantic vector map-based approach for aircraft positioning in GNSS/GPS denied large-scale environment

Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.

Improved Kalman filter method considering multiple factors and its application in landslide prediction

Landslides,seriously threatening human lives and environmental safety,have become some of the most catastrophic natural disasters in hilly and mountainous areas worldwide.Hence,it is necessary to forecast landslide deformation for landslide risk reduction.This paper presents a method of predicting landslide displacement,i.e.,the improved multi-factor Kalman filter(KF)algorithm.The developed model has two advantages over the traditional KF approach.First,it considers multiple external environmental factors(e.g.,rainfall),which are the main triggering factors that may induce slope failure.Second,the model includes random disturbances of triggers.The proposed model was constructed using a time series which consists of over 16-month of data on landslide movement and precipitation collected from the Miaodian loess landslide monitoring system and nearby meteorological stations in Shaanxi province,China.Model validation was performed by predicting movements for periods of up to 7 months in the future.The performance of the developed model was compared with that of the improved single-factor KF,multi-factor KF,multi-factor radial basis function,and multi-factor support vector regression approaches.The results show that the improved multi-factor KF method outperforms the other models and that the predictive capability can be improved by considering random disturbances of triggers.

Distributed Plume Source Localization Using Hierarchical Sensor Networks

A hierarchical wireless sensor networks(WSN) was proposed to estimate the plume source location.Such WSN can be of tremendous help to emergency personnel trying to protect people from terrorist attacks or responding to an accident.The entire surveillant field is divided into several small sub-regions.In each sub-region,the localization algorithm based on the improved particle filter(IPF) was performed to estimate the location.Some improved methods such as weighted centroid,residual resampling were introduced to the IPF algorithm to increase the localization performance.This distributed estimation method eliminates many drawbacks inherent with the traditional centralized optimization method.Simulation results show that localization algorithm is efficient for estimating the plume source location.

Combined centralized and decentralized control for high-precision spacecraft

The improved structural filter combined with Positive Position Feedback(PPF) controller is investigated for high-precision attitude control of flexible spacecraft which consists of rigid central body and flexible appendages.PPF controller is adopted for high frequency vibration suppression,while the improved structural filter is used for suppression of low frequency vibration.After introducing PPF controller,the vibration frequencies are changed.In view of the frequency uncertainties,an improved structural filter is designed,and the stability study for the centralized control system is conducted.The simulation results show that the performance of spacecraft control system is improved,and the control inputs remain unchanged.

Improved multilevel filters to enhance infrared small target

We propose improved multilevel filters （IMLFs） involving the absolute value operation into the algorithmic framework of traditional multilevel filters （MLFs） to improve the robustness of infrared small target enhancement techniques under a complex infrared cluttered background. Compared with the widely used small target enhancement methods which only deal with bright targets, the proposed technique can enhance the infrared small target, whether it is bright or dark. Experimental results verify that the proposed technique is efficient and practical.

Application of wavelet scale correlation filtering and its improved algorithm in signal processing with a spark sound source

It is seriously interfered by ship noise when analyzing and extracting broadband spark sound source signal. In the energy concentrated domain which is below 5 kHz, the traditional scale correlation filtering algorithm, which is based on adjacent-scale correlation, has limited anti-interference ability due to the low signal-to-noise ratio （SNR） and similar Lipschitz exponent characteristic of each other. However, because different frequency bands of the broadband electric spark signal have different noise interferences, the filtering algorithm based on adjacent-scale correlation is adapted to high SNR and small-scale high-frequency wavelet coefficients filtering; the filtering algorithm based on cross-scale correlation is adapted to low SNR and large-scale low-frequency wavelet coefficients filtering, and the threshold coefficient selection method had been corrected in the algorithm. It is shown that the filtering algorithm has a good filtering effect and extracts the broadband spark sound source signal effectively; it is applicable to broadband underwater acoustic signM processing in the presence of narrow-band strong interference background noise.

An optimized baseflow separation method for assessment of seasonal and spatial variability of baseflow and the driving factors

Baseflow is an important component of river or streamflow.It plays a vital role in water utilization and management.An improved Eckhardt recursive digital filter(IERDF)is proposed in this study.The key filter parameter and maximum baseflow index(BFImax)were estimated using the minimum smoothing method to improve baseflow estimation accuracy.The generally considered BFImax of 0.80,0.50 and 0.25 according to the drainage basin’s predominant geological characteristics often leads to significant errors in the regions that have complex subsurface and hydrologic conditions.The IERDF improved baseflow estimation accuracy by avoiding arbitrary parameter values.The proposed method was applied for baseflow separation in the upstream of Yitong River,a tributary of the Second Songhua River,and its performance was evaluated by comparing the results obtained using isotope-tracer data.The performance of IERDF was also compared with nine baseflow separation techniques belonging to filter,BFI and HYSEP methods.The IERDF was also applied for baseflow separation and calculation of rainfall infiltration recharge coefficient at different locations along the Second Songhua River’s mainstream for the period 2000–2016.The results showed that the minimum smoothing method significantly improved BFImax estimation accuracy.The baseflow process line obtained using IEDRF method was consistent with that obtained using isotope 18 O.The IERDF estimated baseflow also showed stability and reliability when applied in the mainstream of the Second Songhua River.The BFI alone in the river showed an increase from the upstream to the downstream.The proportion of baseflow to total flow showed a decrease with time.The intra-annual variability of BFI was different at different locations of the river due to varying climatic conditions and subsurface characteristics.The highest BFI was observed at the middle reaches of the river in summer due to a water surplus from power generation.The research provided valuable information on baseflow characteristics and runoff mode determination,which can be used for water resources assessment and optimization of economic activity distribution in the region.

A combined image matching method for Chinese optical satellite imagery

Image matching is one of the key technologies for digital Earth.This paper presents a combined image matching method for Chinese satellite images.This method includes the following four steps:(1)a modified Wallis-type filter is proposed to determine parameters adaptively while avoiding over-enhancement;(2)a mismatch detection procedure based on a global-local strategy is introduced to remove outliers generated by the Scale-invariant feature transform algorithm,and geometric orientation with bundle block adjustment is employed to compensate for the systematic errors of the position and attitude observations;(3)we design a novel similarity measure(distance,angle and the Normalized Cross-Correlation similarities,DANCC)which considers geometric similarity and textural similarity;and(4)we introduce a hierarchical matching strategy to refine the matching result level by level.Four typical image pairs acquired from Mapping Satellite-1,ZY-102C,ZY-3 and GeoEye-1,respectively,are used for experimental analysis.A comparison with the two current main matching algorithms for satellite imagery confirms that the proposed method is capable of producing reliable and accurate matching results on different terrains from not only Chinese satellite images,but also foreign satellite images.

A Control Strategy of Frequency Self-adaptation Without Phase-locked Loop for VSC-HVDC

A control strategy of frequency self-adaptation without phase-locked loop(PLL)underαβstationary reference frame(αβ-SRF)for a VSC-HVDC system is presented to improve the operational performance of the system under severe harmonic distortion conditions.The control strategy helps to eliminate the cross-coupling under dq synchronous reference frame(dq-SRF),and is achieved through two key technologies:1)positive phase sequence(PPS)and negative phase sequence(NPS)fundamental components are extracted from the AC grid voltage with an improved multiple complex coefficient filter(IMCF),and 2)grid instantaneous frequency is rapidly and precisely tracked using a frequency self-adaptation tracking algorithm(FATA)without PLL.The proposed strategy is applied to a point-to-point VSCHVDC system and validated by means of simulations.The results are compared to those with the traditional vector control strategy under dq-SRF.Simulation results illustrate that the proposed strategy results in better system performance than that with the traditional strategy in terms of harmonic suppression under normal and severe operating conditions of the AC system.