Electrical & Electronics Engineering

Permanent URI for this collectionhttps://hdl.handle.net/10679/44

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3B kamera takibi için eylemsizlik algılayıcılarının birleştirilmesi
(IEEE, 2012) Özer, N.; Erdem, Tanju; Ercan, Ali Özer; Eroğlu Erdem, Ç.; Electrical & Electronics Engineering; Computer Science; ERDEM, Arif Tanju; ERCAN, Ali Özer
It is well known in a Bayesian filtering framework, the use of inertial sensors such as accelerometers and gyroscopes improves 3D tracking performance compared to using camera measurements only. The performance improvement is more evident when the camera undergoes a high degree of motion. However, it is not well known whether the inertial sensors should be used as control inputs or as measurements. In this paper, we present the results of an extensive set of simulations comparing different combinations of using inertial sensors as control inputs or as measurements. We show that it is better use a gyroscope as a control input while an accelerometer can be used as a measurement or control input. We also derive and present the extended Kalman filter (EKF) equations for a specific case of fusing accelerometer and gyroscope data that has not been reported before.
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Analysis of asynchronous cognitive radio system with imperfect sensing and bursty primary user traffic
(Springer Science+Business Media, 2016-03) Ercan, Ali Özer; Electrical & Electronics Engineering; ERCAN, Ali Özer
This paper presents a theoretical analysis of the spectrum utilization levels in a cognitive radio system. We assume that the traffic of the primary network is bursty and asynchronous with the secondary network, which performs imperfect spectrum sensing. Collisions of the primary and the secondary packets are assumed to result in increased packet error probabilities. We present primary and secondary utilization levels under optimized secondary transmission periods for varying primary traffic characteristics and secondary sensing performance levels. The results are also validated by extensive Monte Carlo simulations. We find that an asynchronous cognitive radio network with imperfect spectrum sensing is feasible when optimized transmission periods are used. The effects of primary traffic’s burst pattern and secondary sensing performance are discussed.
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Bağlanırlık aracılığı için kütüphane desteği
(IEEE, 2011) Yazıcı, Volkan; Parsa, A.; Burghardt, F. L.; Rabaey, J. M.; Wolisz, A.; Ercan, Ali Özer; Electrical & Electronics Engineering; Computer Science; ERCAN, Ali Özer; YAZICI, Volkan
The growth of wireless communications has brought about the problem of interference. The realization of future wireless applications that require high data rate and service quality greatly depends on the alleviation of the interference problem. To this end, collaborative resource allocation between different wireless technologies has become an important technique. We have been designing a software architecture that we call “connectivity brokerage”, that will enable this collaboration. In this paper we explain the connectivity brokerage software architecture, and two parts of it; namely WAPI and distributed repository (CBDR) software libraries.
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Bispectrum estimation using a MISO autoregressive model
(Springer International Publishing, 2016) Erdem, Tanju; Ercan, Ali Özer; Electrical & Electronics Engineering; Computer Science; ERDEM, Arif Tanju; ERCAN, Ali Özer
Bispectra are third-order statistics that have been used extensively in analyzing nonlinear and non-Gaussian data. Bispectrum of a process can be computed as the Fourier transform of its bicumulant sequence. It is in general hard to obtain reliable bicumulant samples at high lags since they suffer from large estimation variance. This paper proposes a novel approach for estimating bispectrum from a small set of given low lag bicumulant samples. The proposed approach employs an underlying MISO system composed of stable and causal autoregressive components. We provide an algorithm to compute the parameters of such a system from the given bicumulant samples. Experimental results show that our approach is capable of representing non-polynomial spectra with a stable underlying system model, which results in better bispectrum estimation than the leading algorithm in the literature.
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Color filters: When “optimal” is not optimal
(IEEE, 2016) Trussell, H. J.; Ercan, Ali Özer; Kingsbury, N. G.; Electrical & Electronics Engineering; ERCAN, Ali Özer
It is well known that many more than three or four spectral measurements are required for accurate measurement of color. Previous work has shown seven to ten measurements can yield accurate results on average, but with significant numbers of errors above the threshold of obvious visual detection. Furthermore, the filters used for these measurements are very difficult to fabricate. We show that such filters are not needed and, in fact, have much poorer performance, in perceptual quality measured in ΔEab, than simple narrow-band filters. This is especially true in the presence of Poisson noise at a level common in current digital cameras. In realistic Poisson noise, our filter sets of up to 12 filters allow average ΔEab values around 0.5, with maximum errors below 3.
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Connectivity brokerage: from coexistence to collaboration
(IEEE, 2010) Parsa, A.; Ercan, Ali Özer; Malagon, P.; Burghardt, F.; Rabaey, J. M.; Wolisz, A.; Electrical & Electronics Engineering; ERCAN, Ali Özer
The explosive growth in the density of wirelessly connected devices and their traffic load is creating interference and gradually leading to a severe spectrum shortage. Approaches to address this challenge include dynamic spectrum allocation (cognitive radio) and pro-active interference mitigation strategies requiring coordination between heterogeneous networking technologies. This paper describes a modular and scalable methodology and architecture, called Connectivity Brokerage, that enables proactive co-existence and collaboration between diverse technologies, making joint optimization of the scarce spectrum resources possible.
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Dağıtık bir openflow kontrol birimi mimarisi
(IEEE, 2012) Yazıcı, Volkan; Sunay, Mehmet Oğuz; Ercan, Ali Özer; Electrical & Electronics Engineering; Computer Science; ERCAN, Ali Özer; SUNAY, Mehmet Oğuz; YAZICI, Volkan
Considering the modern internet traffic rates, the network architecture is of particular importance as the running services itself. On the other hand, due to the increasing complexity and black-box structure of the available networking hardware (switches, routers, etc.), the necessary network innovation imposed by the running services becomes infeasible in practice. The software-defined networking notion introduced to solve this problem and one of its emerging and powerful implementations, the OpenFlow protocol, advocate the idea of providing the control and data paths in separate planes. A network operating system running on this control plane, is anticipated to provide necessary measures for scalability and reliability in order to stand against the gigantic traffic pumped by the network. In this paper, we propose a distributed OpenFlow network operating system built with necessary scalability and reliability qualifications without requiring any changes to the existing OpenFlow protocol and networking equipment.
Open Access
Design and implementation of dual band microstrip patch antenna for WLAN energy harvesting system
(2018-07) Amjad, Osama; Munir, Syeda Wajiha; Imeci, S. T.; Ercan, Ali Özer; Electrical & Electronics Engineering; ERCAN, Ali Özer; Amjad, Osama; Munir, Syeda Wajiha
Since the demand for self-sustained wireless systems is increasing, there is a trend towards RF energy harvesting. It is a key solution to energize the low power systems such as the Internet of Things (IoT) devices without replacing the batteries periodically. This paper presents the design and analysis of RF energy harvesting system that consists of dual-band microstrip patch antenna operating at 2.4 GHz and 5.8 GHz, an impedance matching network, 4-stage voltage doubler and a storing circuit. The antenna is designed using ADS Agilent and sonnet suites software that provides a directivity of 5.5 dBi and 6.3 dBi at 2.4 GHz and 5.8 GHz respectively. The measured results of the fabricated antenna are well agreement with the simulated results. Simulated results show that for an input received power of 10 mW, the proposed system can provide 4.5 mW power at the output of 4-stage voltage rectifier with an overall efficiency of 45%.
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Effect of camera-IMU displacement calibration error on tracking performance
(IEEE, 2015) Maxudov, Nekruzjon; Ercan, Ali Özer; Erdem, Tanju; Electrical & Electronics Engineering; Computer Science; ERCAN, Ali Özer; ERDEM, Arif Tanju; Maxudov, Nekruzjon
Due to their complementary properties, inertial measurement units (IMU) and cameras are used in ego-motion tracking applications. For this, the relative rotation and displacement between the camera and IMU reference frames has to be known. There are established methods for the accurate estimation of the relative orientation, however, accurate estimation of the displacement is still a challenging problem. When this is not possible, one might resort to the alternative approach of fusing camera and gyroscope data only, as this does not require the displacement information. To be able to asses such alternatives, this paper presents a systematic methodology based on realistic simulations to analyze the effect of the camera - IMU displacement calibration error on tracking performance, and discusses in detailed simulations the dependency of tracker performance metrics on the camera - IMU displacement's magnitude and calibration error.
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Energy sensing strategy optimization for opportunistic spectrum access
(IEEE, 2012-06) Ercan, Ali Özer; Sunay, Mehmet Oğuz; Electrical & Electronics Engineering; Computer Science; ERCAN, Ali Özer; SUNAY, Mehmet Oğuz
This paper introduces a correlator-based energy sensing strategy for opportunistic spectrum access in a slow, flat-fading channel. The correlator provides weighted energy accumulation in time. We assume that the noise variance is known and the primary user (PU) traffic follows a two state Markov chain with known idle and busy rates. Using Chebyshev bounds on missed detection and false alarm probabilities, we find that the optimal weighting function is an increasing function of time and its shape is dependent on the PU traffic characteristics and SNR. We show that the traditional flat-integration based energy collection method is suboptimal both in the error probability and channel utilization sense.
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Experimental investigation of the impact on TCP traffic by hidden video-tagged UDP traffic
(IEEE, 2017) Çakmak, Kıvanç; Sunay, Mehmet Oğuz; Ercan, Ali Özer; İlhan, C.; Çakar, C.; Sofuoğlu, Ç.; Electrical & Electronics Engineering; Computer Science; SUNAY, Mehmet Oğuz; ERCAN, Ali Özer; Çakmak, Kıvanç
This paper investigates the impact of video-tagged UDP traffic on best-effort TCP traffic in an experimental setup with a novel observation approach. Our setup consists of three 802.11ac nodes in a hidden node topology, where a 20Mbps UDP and a best effort TCP traffic flow from the edge (hidden) nodes to the center node. We observe that, even though the RTS/CTS mechanism is enabled, when UDP and TCP traffic flow simultaneously, video-tagged UDP traffic causes the besteffort TCP traffic throughput to drop by 50%. An analysis of the captured and synchronized packet data reveals for the first time that, the following event is a surprising major contributor to the throughput degradation. Since the TCP and UDP sources are hidden from each other, an RTS packet of the UDP source may collide with the CTS reply to the TCP source. This in turn may result in many collisions between the subsequent RTS packets of the UDP source and the data packet of the TCP source. This paper experimentally shows that this event is particularly commonplace for video-tagged traffic, having smaller back-off duration, severely impacting the cross-traffic.
Open Access
Fusing inertial sensor data in an extended kalman filter for 3D camera tracking
(IEEE, 2015-02) Erdem, Tanju; Ercan, Ali Özer; Electrical & Electronics Engineering; Computer Science; ERDEM, Arif Tanju; ERCAN, Ali Özer
In a setup where camera measurements are used to estimate 3D egomotion in an extended Kalman filter (EKF) framework, it is well-known that inertial sensors (i.e., accelerometers and gyroscopes) are especially useful when the camera undergoes fast motion. Inertial sensor data can be fused at the EKF with the camera measurements in either the correction stage (as measurement inputs) or the prediction stage (as control inputs). In general, only one type of inertial sensor is employed in the EKF in the literature, or when both are employed they are both fused in the same stage. In this paper, we provide an extensive performance comparison of every possible combination of fusing accelerometer and gyroscope data as control or measurement inputs using the same data set collected at different motion speeds. In particular, we compare the performances of different approaches based on 3D pose errors, in addition to camera reprojection errors commonly found in the literature, which provides further insight into the strengths and weaknesses of different approaches. We show using both simulated and real data that it is always better to fuse both sensors in the measurement stage and that in particular, accelerometer helps more with the 3D position tracking accuracy, whereas gyroscope helps more with the 3D orientation tracking accuracy. We also propose a simulated data generation method, which is beneficial for the design and validation of tracking algorithms involving both camera and inertial measurement unit measurements in general.
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Görünüş temelli̇ örtüşme gözeten 3D nesne taki̇bi̇
(IEEE, 2012) Topçu, O.; Ercan, Ali Özer; Alatan, A.; Electrical & Electronics Engineering; ERCAN, Ali Özer
Object tracking is an important element of computer vision algorithms. This problem is difficult due to occlusion, illumination changes and shadows. We propose an appearance based occlusion-aware method for object tracking. Proposed method is based on particle filter tracking in a multi-camera environment. In this method, observations involving both position and appearance information are evaluated depending on whether the corresponding objects are involved in occlusion or not. Tracking is done using state vector in 3D coordinates and probabilities that objects are occluded is estimated to elevate tracking performance. Particles are graded according to their positions and appearances by taking occlusions into account. Weighting particles in terms of position information allows particles to imitate object position and motion. Appearance information help recognize objects after occlusion and track objects when position information is not available. In case of occlusion, particles are weighted according to occlusion probability in order not to make them affected by possibly false measurements. Appearance information is updated by time to account for appearance changes. Appearance is not updated if the object is involved in occlusion. Experiments with PETS and EPFL datasets revealed the success of proposed method and that our method can be applied to different camera configurations.
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Kamera ve ataletsel ölçüm birimi iç kalibrasyonu
(IEEE, 2013) Erdem, Tanju; Ercan, Ali Özer; Aydın, T.; Electrical & Electronics Engineering; Computer Science; ERDEM, Arif Tanju; ERCAN, Ali Özer
In this paper, we address the problem of internal calibration of a camera and an inertial measurement unit (IMU). The internal calibration of a camera and an IMU requires the determination of the relative orientation and displacement between the camera and the IMU. Although the problem of orientation estimation is well studied, and there exists simple algorithms for it, current displacement estimation techniques require very special data collection setups or particular sensor movements. We propose a novel method for estimating the displacement between the camera and an IMU. Our method has a very simple data collection step and involves the solution of linear equations only. Experimental results with real data show the effectiveness of our proposed algorithm.
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Object tracking in the presence of occlusions using multiple cameras: a sensor network approach
( Association for Computing Machinery, 2013) Ercan, Ali Özer; El Gamal, A.; Guibas, L. J.; Electrical & Electronics Engineering; ERCAN, Ali Özer
This article describes a sensor network approach to tracking a single object in the presence of static and moving occluders using a network of cameras. To conserve communication bandwidth and energy, we combine a task-driven approach with camera subset selection. In the task-driven approach, each camera first performs simple local processing to detect the horizontal position of the object in the image. This information is then sent to a cluster head to track the object. We assume the locations of the static occluders to be known, but only prior statistics on the positions of the moving occluders are available. A noisy perspective camera measurement model is introduced, where occlusions are captured through occlusion indicator functions. An auxiliary particle filter that incorporates the occluder information is used to track the object. The camera subset selection algorithm uses the minimum mean square error of the best linear estimate of the object position as a metric, and tracking is performed using only the selected subset of cameras.Using simulations and preselected subsets of cameras, we investigate (i) the dependency of the tracker performance on the accuracy of the moving occluder priors, (ii) the trade-off between the number of cameras and the occluder prior accuracy required to achieve a prescribed tracker performance, and (iii) the importance of having occluder priors to the tracker performance as the number of occluders increases. We find that computing moving occluder priors may not be worthwhile, unless it can be obtained cheaply and to high accuracy. We also investigate the effect of dynamically selecting the subset of camera nodes used in tracking on the tracking performance. We show through simulations that a greedy selection algorithm performs close to the brute-force method and outperforms other heuristics, and the performance achieved by greedily selecting a small fraction of the cameras is close to that of using all the cameras.
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Occlusion-aware 3D multiple object tracker with two cameras for visual surveillance
(IEEE, 2014) Topçu, O.; Alatan, A. A.; Ercan, Ali Özer; Electrical & Electronics Engineering; ERCAN, Ali Özer
An occlusion-aware multiple deformable object tracker for visual surveillance from two cameras is presented. Each object is tracked by a separate particle filter tracker, which is initiated upon detection of a new person and terminated when s/he leaves the scene. Objects are considered as 3D points at their centre of masses as if their mass density is uniform. Point objects and corresponding silhouette centroids in two views together with the epipolar geometry they satisfy resulted in a practical tracking methodology. An occlusion filter is described, that provides the tracker filters conditional occlusion probabilities of the objects, given their estimated positions. Advances over the previous work; in the computation of conditional occlusion probabilities, in incorporation of these probabilities in the particle filter, and in maintaining tracking of separating objects after long periods of moving close-by, are presented on PETS 2006, PETS 2009 and EPFL datasets.
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On sensor fusion for head tracking in augmented reality applications
(IEEE, 2011) Ercan, Ali Özer; Erdem, Tanju; Electrical & Electronics Engineering; Computer Science; ERCAN, Ali Özer; ERDEM, Arif Tanju
The paper presents a simple setup consisting of a camera and an accelerometer located on a head mounted display, and investigates the performance of head tracking for augmented reality applications using this setup. The information from the visual and inertial sensors is fused in an extended Kalman filter (EKF) tracker. The performance of treating accelerometer measurements as control inputs is compared to treating both camera and accelerometer measurements as measurements, i.e., fusing them in the measurement update stage of the EKF simultaneously. It is concluded via simulations that treating accelerometer measurements as control inputs performs practically as good as treating both measurements as measurements, while providing a lower complexity tracker.
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On the feasibility of synchronous, retransmission-based cognitive networks
(Elsevier, 2016-01) Ercan, Ali Özer; Sunay, Mehmet Oğuz; Electrical & Electronics Engineering; Computer Science; ERCAN, Ali Özer; SUNAY, Mehmet Oğuz
This paper presents a new, joint Markov chain model for the primary and secondary traffic in a cognitive radio network to assess the feasibility of opportunistic spectrum access for different operational scenarios, validated by extensive realistic Monte-Carlo simulations. Enhancing on the current literature, the generalized model allows for the consideration of a retransmission-based traffic as well as the presence of transmission queues for the primary user. The generalized model also allows for the investigation of the system behavior in the presence of imperfect sensing at the secondary users. The presented model is applicable for all primary user traffic models that use discrete-time Markov chains. An infinitely backlogged secondary user network is considered to investigate the maximum possible network utilization. The paper concludes that a percentile channel occupation of the primary user on its own is not always a sufficient metric to assess whether secondary transmission is feasible. It is shown that the interplay between primary network traffic characteristics, as well as the sensing frequency and probabilities of missed detection and false alarm for the secondary network detector are of primal importance for such feasibility claims. The results reveal that the preferred sensing frequency for the secondary users is a function of the primary user traffic pattern and that the commonly used frequency of sensing every transmission slot is not always optimal. The results also show that when sensing frequency is low, secondary utilization decreases with more bursty primary traffic, whereas the impact on primary utilization becomes less.
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Optimization and analysis of WLAN RF energy harvesting system architecture
(IEEE, 2016) Munir, Syeda Wajiha; Amjad, Osama; Zeydan, E.; Ercan, Ali Özer; Electrical & Electronics Engineering; ERCAN, Ali Özer; Munir, Syeda Wajiha; Amjad, Osama
This paper presents the design, analysis and optimization of RF energy harvesting system for WLAN source operating at 2.4 GHz and 5.8 GHz. The system architecture comprises of RF WLAN source, wireless channel, an efficient dual band microstrip patch antenna, an impedance matching network, 4-stage voltage rectifier and a storing circuit. Matching network ensures the maximum power transfer from source to load. HSMS-2850 Schottky diodes are used in rectifier design, which provide low forward voltage and low substrate leakage. The proposed system design is used to analyze the effect of distance on RF power obtained at receiving side. The size of storage capacitor is chosen carefully such that it can store sufficient amount of charge and takes reasonable charging time. Moreover, the circuit parameters are varied to optimize the designed circuit that provides the maximum efficiency of 45% and 22% at 2.4 GHz and 5.8 GHz respectively, at a distance of 1 meter from source. Simulated results show that for received RF power of 5 dBm the system can provide 1.3 mW power across 10 kΩ load, which can be enough to energize the low power devices. The voltage supplied by the harvesting system can be increased further by increasing the number of stages in voltage rectifier according to the application but at the cost of parasitic loss.
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Rao-Blackwell parçacık süzgeci ile 3 boyutlu insan takibi
(IEEE, 2014) Topçu, O.; Orguner, U.; Alatan, A. A.; Ercan, Ali Özer; Electrical & Electronics Engineering; ERCAN, Ali Özer
Visual tracking has an important place among computer vision applications. Visual tracking with particle filters is a well-known methodology. The performance of particle filters is dependent on efficient sampling of the state space, which in turn, is dependent on number of particles. In this paper, Rao-Blackwell technique is applied to particle filters to improve sampling efficiency. Both algorithms are applied to people tracking problem. Under the same circumstances, the resulting algorithm is demonstrated to perform better than the original algorithm via experiments on the PETS2009 benchmark dataset.

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