Distributed Super Nested Arrays: Reduce the Mutual Coupling between Array Antennas

In array, mutual coupling between the antennas is inevitable, which has an adverse effect on the estimation of parameters. To reduce the mutual coupling between the antennas of distributed nested arrays, this paper proposes a new array called the distributed super nested arrays, which have the good characteristics of the distributed nested arrays and can reduce the mutual coupling between the antennas. Then, an improved multiscale estimating signal parameter via rotational invariance techniques (ESPRIT) algorithm is presented for the distributed super nested arrays to improve the accuracy of direction-of-arrival (DOA) estimation. Next, we analyze the limitations of the spatial smoothing algorithm used by the distributed super nested arrays when there are multiple-source signals and the influence of the baseline length of distributed super nested arrays on the accuracy of DOA estimation. The simulation results show that the distributed super nested arrays can effectively reduce the mutual coupling between the array antennas, improve the DOA estimation performance, and significantly increase the number of detectable source signals.

Trajectory Recording and Analysis System for Cockroach Robot

In this study, We design a trajectory recording and analysis system to record and analysis the changes in the movement behavior of the cockroach robot after stimulation. The external hardware of this system is an infrared touchpad as the experimental platform for the cockroach robot to crawl freely, and the infrared matrices densely distributed in the X and Y directions of the infrared touchpad are used to detect and locate the position of the cockroach robot. The cockroach robot's movement trajectory is displayed visually through the projector's interface projection on the infrared touchpad. The system software consists of three main parts: the electrical signal parameter setting module, the movement trajectory recording module, and the data analysis module. The electrical signal parameter setting module sets the stimulation parameters and configures the corresponding serial port to independently stimulate the left and right antenna and cercus of the cockroach; the trajectory recording module is used to record the trajectory of the cockroach robot through the coordinate positioning method. The data analysis module explores the change of motion behavior of the cockroach robot with time after receiving the stimulus by using the stage analysis method, and explores the change of motion of the cockroach robot with different voltage stimulus by using the module analysis method. The system is tested in experiments and the results demonstrated its applicability to the recording and analysis of the cockroach robot's trajectories.

DEVELOPMENT OF AN ALGORITHM FOR IDENTIFICATION OF TERRAIN IN A LOWER LIMB PROSTHESIS CONTROL SYSTEM

Статья посвящена разработке алгоритма определения типа местности, по которой перемещается пользователь протезом нижней конечности. Идентификация местности, по которой происходит движение, является важной задачей при управлении протезами нижних конечностей, так как на разных типах местности протез должен совершать разные модели движений. В данном исследовании высказано предположение о возможности определения типа местности с помощью электромиографических датчиков, которые записывают сигналы от определенных мышц пользователя протезом. Чтобы подтвердить это утверждение, было проведено исследование. Испытуемые выполняли несколько типов движений: движение прямо, подъем и спуск по лестнице, подъем и спуск по наклонной поверхности. Электромиографические сигналы регистрировались от разных мышц нижних конечностей испытуемых. После первичной обработки из сигналов были выделены параметры биоэлектрического сигнала, чаще всего используемые в управлении протезами. Результаты исследования показали, что существует статистическая разница в некоторых параметрах сигнала в зависимости от канала регистрации сигнала и типа местности, на которой происходит движение. Исследование доказало возможность определения типа местности по четырем комбинациям параметр сигнала - мышца. На основании полученных результатов предложен алгоритм идентификации местности The article is devoted to the development of an algorithm for determining the type of terrain along which the user moves with a lower limb prosthesis. Identification of the terrain along which the movement takes place is when controlling the prostheses of the lower extremities, since on different types of terrain the prosthesis must perform different models of movements. In this study, it is assumed that it is possible to determine the location using electromyographic sensors that record signals from the muscles of the wearer with a prosthesis. Research has been done to confirm this claim. The subjects performed several types of movements: straight movement, climbing and descending stairs, ascending and descending an inclined surface. Electromyographic signals were recorded from different muscles of the lower end objects. After primary processing, the parameters of the bioelectric signal were extracted from the signals. The research results show that there is a statistical difference in some signal parameters depending on the signal registration channel and the type of terrain on which the movement takes place. The study proved the possibility of determining the type of terrain by four combinations of signal parameter - muscle. Based on the results obtained, an algorithm for identifying the area is proposed

Vibration Signal Parameter Estimation in Variable Speed: Algorithms and performance bounds

Vibration signal parameter estimation for rotating machinery diagnostics operating under variable speedconditions is considered. At first, we provide a brief survey of existing methods for Quadratic Phase Signal (QPS)parameter estimation. Then, we introduce improved solutions for the general QPS case and the Order QPS (O-QPS)case, respectively. For all considered cases (namely the QPS, O-QPS with tachometer and O-QPS without tachometer),we develop the Cramer Rao Bounds to assess and compare the estimation performance limits for each model. Finally, wecompare the performance of all considered methods and highlight, in particular, the gain of the proposed solutions.

Joint Doppler Shift and Time Delay estimation by Decovonlution of Generalized Matched Filter

Resolution probability is the most important indicator for signal parameter estimator, including estimating time delay, and joint Doppler shift and time delay. In order to get high resolution probability, some procedures have been suggested such as compressed sensing. Based on the signal's sparsity, compressed sensing has been used to estimate signal parameter in recent research. After solving $\ell_0$ Norm Optimization problem, the methods would achieve high resolution. These methods all require high SNR. In order to improve the performance in low SNR, a novel implementation is proposed in this paper. We give a sparsity representation for the generalized matched filter output, or ambiguity function, while the former methods utilized the sparsity representation for channel response. By deconvolving the generalized matched filter output, 2D estimation for Doppler shift and time delay would be gotten by greedy method, optimization method based on relaxation, or Bayesian method. Simulation demonstrates our method has better performance in low SNR than the method by the channel sparsity representation.