In pursuit of high resolution radar using pursuit algorithms

Radar receivers typically employ matched filters designed to maximize signal to noise ratio (SNR) in a single target environment. In a multi-target environment, however, matched filter estimates of target environment often consist of spurious targets because of radar signal sidelobes. As a result, matched filters are not suitable for use in high resolution radars operating in multi-target environments. Assuming a point target model, we show that the radar problem can be formulated as a linear under-determined system with a sparse solution. This suggests that radar can be considered as a sparse signal recovery problem. However, it is shown that the sensing matrix obtained using common radar signals does not usually satisfy the mutual coherence condition. This implies that using recovery techniques available in compressed sensing literature may not result in the optimal solution. In this thesis, we focus on the greedy algorithm approach to solve the problem and show that it naturally yields a quantitative measure for radar resolution. In addition, we show that the limitations of the greedy algorithms can be attributed to the close relation between greedy matching pursuit algorithms and the matched filter. This suggests that improvements to the resolution capability of the greedy pursuit algorithms can be made by using a mismatched signal dictionary. In some cases, unlike the mismatched filter, the proposed mismatched pursuit algorithm is shown to offer improved resolution and stability without any noticeable difference in detection performance. Further improvements in resolution are proposed by using greedy algorithms in a radar system using multiple transmit waveforms. It is shown that while using the greedy algorithms together with linear channel combining can yield significant resolution improvement, a greedy approach using nonlinear channel combining also shows some promise. Finally, a forward-backward greedy algorithm is proposed for target environments comprising of point targets as well as extended targets

IMU Aided GPS Based Navigation of Ackermann Steered Rover

GPS signal loss is a major issue when the navigation system of rovers is based solely on GPS for outdoor navigation rendering the rover stuck in the mid of the road in case of signal loss. In this study, a low-cost IMU aided GPS-based navigation system for Ackermann Steered mobile robots is presented and tested to cater to the issue of GPS signal loss along. GPS path is selected and fed using the android application which provides real-time location tracking of the rover on the map embedded into the application. System utilizes Arduino along with the node MCU, compass, IMU, Rotary encoders, and an Ackermann steered rover. Contorller processes the path file, compares its current position with the path coordinates and navigates using inertial sensor aided navigation algorithm, avoiding obstacles to reach its destination. IMU measures the distance traveled from each path point, and in case of signal loss, it makes the rover move for the remaining distance in the direction of destination point. Rover faced a sinusoidal motion due to the steering, so PID was implemented. The system was successfully tested on the IST premises and finds its application in the delivery trolley, institutional delivery carts, and related applications

IMU Aided GPS Based Navigation of Ackermann Steered Rover

GPS signal loss is a major issue when the navigation system of rovers is based solely on GPS for outdoor navigation rendering the rover stuck in the mid of the road in case of signal loss. In this study, a low-cost IMU aided GPS-based navigation system for Ackermann Steered mobile robots is presented and tested to cater to the issue of GPS signal loss along. GPS path is selected and fed using the android application which provides real-time location tracking of the rover on the map embedded into the application. System utilizes Arduino along with the node MCU, compass, IMU, Rotary encoders, and an Ackermann steered rover. Contorller processes the path file, compares its current position with the path coordinates and navigates using inertial sensor aided navigation algorithm, avoiding obstacles to reach its destination. IMU measures the distance traveled from each path point, and in case of signal loss, it makes the rover move for the remaining distance in the direction of destination point. Rover faced a sinusoidal motion due to the steering, so PID was implemented. The system was successfully tested on the IST premises and finds its application in the delivery trolley, institutional delivery carts, and related applications

A Comparative Analysis of Wi-Fi Offloading and Cooperation in Small-Cell Network

Small cells deliver cost-effective capacity and coverage enhancement in a cellular network. In this work, we present the interplay of two technologies, namely Wi-Fi offloading and small-cell cooperation that help in achieving this goal. Both these technologies are also being considered for 5G and B5G (Beyond 5G). We simultaneously consider Wi-Fi offloading and small-cell cooperation to maximize average user throughput in the small-cell network. We propose two heuristic methods, namely Sequential Cooperative Rate Enhancement (SCRE) and Sequential Offloading Rate Enhancement (SORE) to demonstrate cooperation and Wi-Fi offloading, respectively. SCRE is based on cooperative communication in which a user data rate requirement is satisfied through association with multiple small-cell base stations (SBSs). However, SORE is based on Wi-Fi offloading, in which users are offloaded to the nearest Wi-Fi Access Point and use its leftover capacity when they are unable to satisfy their rate constraint from a single SBS. Moreover, we propose an algorithm to switch between the two schemes (cooperation and Wi-Fi offloading) to ensure maximum average user throughput in the network. This is called the Switching between Cooperation and Offloading (SCO) algorithm and it switches depending upon the network conditions. We analyze these algorithms under varying requirements of rate threshold, number of resource blocks and user density in the network. The results indicate that SCRE is more beneficial for a sparse network where it also delivers relatively higher average data rates to cell-edge users. On the other hand, SORE is more advantageous in a dense network provided sufficient leftover Wi-Fi capacity is available and more users are present in the Wi-Fi coverage area

Design and Development of a Near Isotropic Printed Arc Antenna for Direction of Arrival (DoA) Applications

This research presents an easy to fabricate isotropic printed arc antenna element to be used for direction of arrival (DoA) arrays. The proposed antenna exhibits a total gain variation of 0.5 dB over the entire sphere for 40 MHz impedance bandwidth at 1 GHz, which is the best design isotropy reported in literature so far. In addition, the isotropic bandwidth of the antenna for total gain variation of ≤3 dB is 225 MHz with 86% efficiency. The isotropic wire antenna is first designed and simulated in Numerical Electromagnetic code (NEC). An equivalent printed antenna is then simulated in CST, where single (short circuited) stub is integrated with the antenna for input matching and the results of NEC simulations are verified. The planar antenna is then manufactured using FR4 substrate for measurements. Good agreement between the measured and simulated results is observed, however the total gain variation is increased to 2 dB for the fabricated antenna. This is because of the unavoidable field scattering from the antenna substrate, the feed cables, and the antenna testing platform

Purdue Terrestrial Observatory Activities

Recent Purdue Terrestrial Observatory (PTO) activities (in data acquisition and access, hardware, partnerships, other) are described in overview

Hyperspectral anomaly detection: a performance comparison of existing techniques

Anomaly detection in Hyperspectral Imagery (HSI) has received considerable attention because of its potential application in several areas. Numerous anomaly detection algorithms for HSI have been proposed in the literature; however, due to the use of different datasets in previous studies, an extensive performance comparison of these algorithms is missing. In this paper, an overview of the current state of research in hyperspectral anomaly detection is presented by broadly dividing all the previously proposed algorithms into eight different categories. In addition, this paper presents the most comprehensive comparative analysis to-date in hyperspectral anomaly detection by evaluating 22 algorithms on 17 different publicly available datasets. Results indicate that attribute and edge-preserving filtering-based detection (AED), local summation anomaly detection based on collaborative representation and inverse distance weight (LSAD-CR-IDW) and local summation unsupervised nearest regularized subspace with an outlier removal anomaly detector (LSUNRSORAD) perform better as indicated by the mean and median values of area under the receiver operating characteristic (ROC) curves. Finally, this paper studies the effect of various dimensionality reduction techniques on anomaly detection. Results indicate that reducing the number of components to around 20 improves the performance; however, any further decrease deteriorates the performance