60,169 research outputs found

    Localization Performance of 1-Bit Passive Radars in NB-IoT Applications

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    Location-based services form an important use-case in emerging narrowband Internet-of-Things (NB-IoT) networks. Critical to this offering is an accurate estimation of the location without overlaying the network with additional active sensors. The massive number of devices, low power requirement, and low bandwidths restrict the sampling rates of NB-IoT receivers. In this paper, we propose a novel low-complexity approach for NB-IoT target delay estimation in cases where one-bit analog-to-digital-converters (ADCs) are employed to sample the received radar signal instead of high-resolution ADCs. This problem has potential applications in the design of inexpensive NB-IoT radar and sensing devices. We formulate the target estimation as a multivariate fractional optimization problem and solve it via Lasserre's semi-definite program relaxation. Numerical experiments suggest feasibility of the proposed approach yielding high localization accuracy with a very low number of 1-bit samples

    One-bit target detection in collocated MIMO Radar and performance degradation analysis

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    Target detection is an important problem in multipleinput multiple-output (MIMO) radar. Many existing target detection algorithms were proposed without taking into consideration the quantization error caused by analog-to-digital converters (ADCs). This paper addresses the problem of target detection for MIMO radar with one-bit ADCs and derives a Rao's test-based detector. The proposed method has several appealing features: 1) it is a closed-form detector; 2) it allows us to handle sign measurements straightforwardly; 3) there are closed-form approximations of the detector's distributions, which allow us to theoretically evaluate its performance. Moreover, the closed-form distributions allow us to study the performance degradation due to the one-bit ADCs, yielding an approximate 2 dB loss in the low-signal-to-noise-ratio (SNR) regime compared to 34-bit ADCs. Simulation results are included to showcase the advantage of the proposed detector and validate the accuracy of the theoretical results.The work of David Ramírez was supported in part by the Ministerio de Ciencia e Innovación, jointly with the European Commission (ERDF) under Grant PID2021-123182OB-I00 (EPiCENTER) and in part by the Comunidad de Madrid under Grant Y2018/TCS-4705 (PRACTICO-CM). The work of Lei Huang was supported in part by the National Science Fund for Distinguished Young Scholars under Grant 61925108 and in part by the Joint fund of the National Natural Science Foundation of China and Robot Fundamental Research Center of Shenzhen Government under Grant U1913203

    Generation of topographic terrain models utilizing synthetic aperture radar and surface level data

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    Topographical terrain models are generated by digitally delineating the boundary of the region under investigation from the data obtained from an airborne synthetic aperture radar image and surface elevation data concurrently acquired either from an airborne instrument or at ground level. A set of coregistered boundary maps thus generated are then digitally combined in three dimensional space with the acquired surface elevation data by means of image processing software stored in a digital computer. The method is particularly applicable for generating terrain models of flooded regions covered entirely or in part by foliage

    Goldstone solar system radar signal processing

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    A performance analysis of the planetary radar data acquisition system is presented. These results extend previous computer simulation analysis and are facilitated by the development of a simple analytical model that predicts radar system performance over a wide range of operational parameters. The results of this study are useful to both the radar system designer and the science investigator in establishing operational radar data acquisition parameters which result in the best systems performance for a given set of input conditions

    The economics of data acquisition computers for ST and MST radars

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    Some low cost options for data acquisition computers for ST (stratosphere, troposphere) and MST (mesosphere, stratosphere, troposphere) are presented. The particular equipment discussed reflects choices made by the University of Alaska group but of course many other options exist. The low cost microprocessor and array processor approach presented here has several advantages because of its modularity. An inexpensive system may be configured for a minimum performance ST radar, whereas a multiprocessor and/or a multiarray processor system may be used for a higher performance MST radar. This modularity is important for a network of radars because the initial cost is minimized while future upgrades will still be possible at minimal expense. This modularity also aids in lowering the cost of software development because system expansions should rquire little software changes. The functions of the radar computer will be to obtain Doppler spectra in near real time with some minor analysis such as vector wind determination

    A pseudo-matched filter for chaos

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    A matched filter maximizes the signal-to-noise ratio of a signal. In the recent work of Corron et al. [Chaos 20, 023123 (2010)], a matched filter is derived for the chaotic waveforms produced by a piecewise-linear system. Motivated by these results, we describe a pseudo-matched filter, which removes noise from the same chaotic signal. It consists of a notch filter followed by a first-order, low-pass filter. We compare quantitatively the matched filter's performance to that of our pseudo-matched filter using correlation functions in a simulated radar application. On average, the pseudo-matched filter performs with a correlation signal-to-noise ratio that is 2.0 dB below that of the matched filter. Our pseudo-matched filter, though somewhat inferior in comparison to the matched filter, is easily realizable at high speed (> 1 GHz) for potential radar applications
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