Department Publications

We present a compressive sensing based defect detection by multiple input multiple output (MIMO) wireless radar. Here, defects are inside a layered material structure, therefore, due to reflections from the surface of the layered material structure the defect detection is challenging. By utilizing a low-rank nature of the reflections of the layered material structure and sparse nature of the defects, we propose a method based on rank minimization and sparse recovery. To improve the accuracy in the recovery of low-rank and sparse components, we propose a non-convex approach based on the iteratively reweighted nuclear norm and iteratively reweighted norm algorithm. Our numerical results show that the proposed method is able to demix and recover the signalling responses of the defects and layered structure successfully from substantially reduced number of observations. Further, the proposed approach outperforms the state-of-the-art clutter reduction approaches

In this paper, we are concerned with indoor localization based on multiple-antenna channel measurements. Indoor localization is an active area of research due to its great importance in many applications. We propose a hybrid algorithm which combines the benefits of two techniques, namely signal processing and machine learning. We validate our algorithm based on real measurements acquired from two practical setups. Our approach shows a very promising performance in the IEEE CTW 2019 - Positioning Algorithm Competition where the algorithm achieves an accuracy within RMSE values below 10 cm. We further build a setup in another indoor environment, where the algorithm still proves a very good performance compared to state-of-the art techniques used in indoor localization tasks.

In this letter an intuitive measurement based approximation for packet switched network traffic in backbone links is presented. It consists of a sum of independent non-identical Bernoulli sources. The resulting sum has a Poisson binomial distribution which can be approximated to a skewed Gaussian distribution at the asymptote. It can be further approximated to a binomial distribution for predicting congestion by estimating the number of users of the network. The results are verified using samples of traffic data from 42 academic and research institutions.

We address the problem of identification of spherical objects, which are inside a layered structure by wireless sensing. Here, the backscatter response is used to identify the objects. It is a task, which is improved as the resolution gets higher. Therefore, to have a better resolution we consider the THz band. However, in the THz surface scattering expands the backscatter response of the layered structure in time. Thus, the backscatter response of the objects and the layered structure superimpose each other. This becomes even more severe due to the limited bandwidth at the receiver. In consequence, the exploitation of sophisticated signal separation methods for improved object identification is required. Therefore, we propose morphological component analysis (MCA), semi-blind MCA (MCA-SB) and singular value decomposition (SVD) methods. The MCA and MCA-SB rely on the sparse representation of signals …

In this paper, we introduce a novel algorithm that can dramatically reduce the number of antenna elements needed to accurately predict the direction of arrival (DOA) for multiple input multiple output (MIMO) radar. The new proposed algorithm predicts the received signal of a large antenna setup using reduced number of antenna by using coupled dictionary learning. Hence, this enables the MIMO radar to resolve more paths, which could not be resolved by the fewer antennas. Specifically, we overcome the problem of inaccurate DOA estimation due to a small virtual array setup. For example, we can use dictionary learning to predict 100 virtual array elements using only 25. To evaluate our algorithm, we used multiple signal classification (MUSIC) as a DOA estimation technique to estimate the DOA for non coherent multiple targets. The results show that using the predicted received signal, the proposed algorithm …

This paper proposes a novel channel estimation method and a cluster-based opportunistic scheduling policy, for a wireless energy transfer (WET) system consisting of multiple low-complex energy receivers (ERs) with limited processing capabilities. Firstly, in the training stage, the energy transmitter (ET) obtains a set of Received Signal Strength Indicator (RSSI) feedback values from all ERs, and these values are used to estimate the channels between the ET and all ERs. Next, based on the channel estimates, the ERs are grouped into clusters, and the cluster that has its members closest to its centroid in phase is selected for dedicated WET. The beamformer that maximizes the minimum harvested energy among all ERs in the selected cluster is found by solving a convex optimization problem. All ERs have the same chance of being selected regardless of their distances from the ET, and hence, this scheduling …

This paper focuses on wireless energy transfer (WET) to a pair of low complex energy receivers (ER), by only utilizing received signal strength indicator (RSSI) values that are fed back from the ERs to the energy transmitter (ET). Selecting the beamformer that maximizes the total average energy transfer between the ET and the ERs, while satisfying a minimum harvested energy criterion at each ER, is studied. This is a non-convex constrained optimization problem which is difficult to solve analytically. Also, any analytical solution to the problem should only consists of parameters that the ET knows, or the ET can estimate, as utilizing only RSSI feedback values for channel estimation prohibits estimating some channel parameters. Thus, the paper focuses on obtaining a suboptimal solution analytically. It is proven that if the channels between the ET and the ERs satisfy a certain sufficient condition, this solution is in fact …

Multiple antenna techniques that allow energy beamforming have been looked upon as a possible candidate for increasing the transfer efficiency between the energy transmitter (ET) and the energy receiver in wireless power transfer. This paper introduces a novel scheme that facilitates energy beamforming by utilizing received signal strength indicator (RSSI) values to estimate the channel. First, in the training stage, the ET will transmit using each beamforming vector in a codebook, which is predefined using a Cramer-Rao lower bound analysis. RSSI value corresponding to each beamforming vector is fed back to the ET, and these values are used to estimate the channel through a maximum likelihood analysis. The results that are obtained are remarkably simple, requires minimal processing, and can be easily implemented. The paper also validates the analytical results numerically, as well as experimentally, and …

Many real world stochastic processes are non-stationary, which means that the probability distribution that generates data samples is time-varying. In the context of machine learning, this phenomenon is known as concept drift. It is important that machine learning models are able to adapt to concept drift in order to prevent degradation in accuracy. In this paper, we present two algorithms for drift detection and adaptation. Drift is measured by continuously tracking a difference metric between probability distributions estimated from two sample windows preceding a time point. High values for the difference metric indicates that concept drift has occurred, and the model must be adapted. Adaptation is done by training a new model for the drifted process, and adding it to an ensemble of models. Previously trained models are retained, and their weights in the ensemble are adjusted to reflect similarity with the current …

Accurate attitude estimation in high dynamic motion scenarios like unmanned aerial vehicle navigation or human motion and magnetically disturbed indoor environments requires compensation of accelerometer disturbances as well as magnetometer disturbances. This paper proposes a novel algorithm for accelerometer disturbance rejection by adaptive estimation of accelerometer measurement covariance matrix online. Magnetic disturbances are generally lasting long compared to accelerometer disturbances which are generally short term in indoor navigation environments. Novel two step Kalman filter update method is proposed to separate attitude correction from heading correction. The magnetometer is used only for heading update such that the attitude estimation is not affected by errors in magnetometer measurement. Performances of the proposed algorithms are shown by using real world sensor data.

Pose tracking for outdoor rovers is generally a complex task which is further complicated in conditions where a Global Positioning System (GPS) signal is denied such as in planetary exploration, underground mines and covered areas. In these conditions the rover's pose needs to be calculated purely based on the rover's current environment observations. However, conventional wheel odometry is not reliable on rough terrain where wheels are prone to slip and the wheels do not have a common plane of motion due to suspension systems. This paper proposes a Fast State Variable Extension (Fast-SVE) method in which 2D state variables (x, y, yaw) are extended to the full 3D state (x, y, z, roll, pitch, yaw) to achieve effective real time 3D pose tracking of the rover. A particle filter implementation incorporating the Fast-SVE method is used to track the 3D pose of the rover with roll and pitch values used for weighting. An …

Multiple antenna techniques, that allow energy beamforming, have been looked upon as a possible candidate for increasing the efficiency of the transfer process between the energy transmitter (ET) and the energy receiver (ER) in wireless energy transfer. This paper introduces a novel scheme that facilitates energy beamforming by utilizing Received Signal Strength Indicator (RSSI) values to estimate the channel. Firstly, in the training stage, the ET will transmit sequentially using each beamforming vector in a codebook, which is pre-defined using a Cramer-Rao lower bound analysis. The RSSI value corresponding to each beamforming vector is fed back to the ET, and these values are used to estimate the channel through a maximum likelihood analysis. The results that are obtained are remarkably simple, requires minimal processing, and can be easily implemented. Also, the results are general and hold for all …

Pitch and airspeed responses of a medium scale UAV were identified using the prediction error method. Data collection was conducted with an active closed loop autopilot control system. A naive SISO open loop transfer function was estimated using the parametric direct approach. Since its predictability was not significant, better estimators were developed using MISO parametric direct, and SISO parametric indirect method. The model validations were done to quantify their predictability.

Device free detection and localization is a promising and a very practical research area where installation of expensive sensors and/or tagging the intruder is not feasible. This paper reports a mesh network developed for device free trespasser detection. We use the Received Signal Strength Indicator (RSSI) measurements of the wireless links within the mesh as the sole sensing mechanism. A fingerprint of RSSI measurements characterizes the environment under normal conditions including multi-path effects. A technique to differentiate RSSI variations due to trespassers from those due to multi-path effects is demonstrated. The results of the experiments conducted in an outdoor environment have verified that the proposed method can be used to detect trespassers successfully. The reliability of the detection is improved by cross-correlating RSSI variations among the multiple links in the mesh. The ability to extend …

Difficult conditions on outdoor terrains make outdoor autonomy for rovers, a challenging task. The conventional wheel odometry method uses orientation measurements to assume a momentary plane to apply wheel encoder readings. On uneven terrains, this method often gives poor results for position tracking, and therefore rarely used. To improve the conventional odometry motion model, immediate terrain data can be used. This paper proposes a novel state variable extension (SVE) method to establish a connection between state space variables of a terrain rover by combining terrain point clouds with rover kinematics. The simulation results show that when the 2D state variables (x, y, yaw) are known, the 2D state can be extended to its 3D state (x, y, z, roll, pitch, yaw) with minimal error. The proposed SVE method is employed in a particle filter to determine the 2D state variables, which in turn results in achieving …

quadrotor microaerial vehicles (MAVs) are simple robotic platforms with regard to their construction. In their basic form, they are no more than two counterrotating propeller pairs attached symmetrically to a rigid crosslike frame, along with the means to control the speed of each individual propeller. This symmetric design has enabled the quadrotor to become a simple but powerful vertical takeoff and landing aerial platform popular among the robotics community.

An informative digital map is a prerequisite for future Intelligent Transportation System (ITS) applications such as lane level navigation systems. Preparing and updating such detailed digital maps by using existing methods such as surveying and image digitization is not practical due to the time and cost involved. We propose a method that statistically mines Global Positioning System (GPS) trajectory data obtained from vehicles to generate a lane level digital map of the road. The proposed method is capable of generating a digital map of the road which contains lane centerlines. The proposed method is independent of the lane width, lane parallelism and can handle lane splits and merges. In addition, a method that can be used to generate a map of lane boundaries is also presented. The proposed methods have been tested using the GPS data collected using vehicles equipped with GPS enabled mobile phones …

For high scientific return, planetary rovers need to navigate longer distances autonomously and be less dependent on Earth station. Collaboration between rovers can substantially increase the localization accuracy for all the rovers and therefore, opens up opportunity for future exploration missions. This study aims at introducing a decentralized cooperative SLAM technique for two rovers based on EKF-SLAM and FastSLAM algorithms. Several data fusion methods and motion strategies are formulated. Furthermore, a novel SLAM technique called, cooperative positioning SLAM is proposed. The results show that by fusing information, better localization accuracies can be achieved. To validate algorithms a 3D simulation environment has been developed using opensource tools.

This paper introduces techniques for designing and implementing remotely controllable outdoor robots with the ability to localize itself while traversing in hazardous environments. The robot platform designed is a semi-autonomous tiller modified as required by the application. Localization based on wireless sensor network which has been a research interest of is addressed here with the use of Zigbee protocol. A Kalman filter was applied for the initial gathering of training data. For the improvement of the accuracy of position estimation, a fuzzy inference system is introduced. An extended Kalman filter is applied at the end in order to fuse the encoder data with the filtered RSS data. Results prove that a metric accuracy varying from 2m to 10m is achievable depending on the location of the robot with respect to the sensor nodes.

Developing autonomous mobile robots that can coexist with human in populated environments is still considered a big challenge. To address this problem the authors propose a novel scheme to assist mobile robots by providing localization information externally. This scheme combines the autonomous navigation and target tracking research fields to arrive at a structured assistance system for autonomous mobile robots. In the proposed scheme, the environment is sensed using a laser range finder and a camera based sensor unit. Using the Rao-Blackwellized particle filter technique, the robots that need assistance are continuously tracked. In contrast with conventional laser range finder based tracking systems, the placement of the sensor is changed to a level above average human height and the mobile robots are modified by attaching a cylindrical pole. The experiments showed the validity of the proposed …

A novel single-integral representation for the bivariate Rician distribution was presented in a recent letter in this Transactions (ibid., vol. 59, no. 11. pp. 2951-2954, Nov. 2011). The expression given for the bivariate Rician probability density function (PDF) [1, eq. (12a)] contains a typographical error. The correct expression for the bivariate Rician PDF is presented here.

第 22 回アストロダイナミクスシンポジウム (2012 年 7 月 30-31 日. 宇宙航空研究開発機構宇宙科学研究所 (JAXA)(ISAS)), 相模原市, 神奈川県