Research

19 pages, 3936 KiB

Open AccessArticle

Research and Verification of a Novel Interferometry Method by Joint Processing of Downlink Pseudo-Noise Ranging and DOR Signals for Deep Space Exploration

by Weitao Lu, Min Fan, Lue Chen, Dezhen Xu, Yujia Zhang and Tianpeng Ren

Sensors 2024, 24(3), 822; https://doi.org/10.3390/s24030822 - 26 Jan 2024

Viewed by 497

Abstract

The remarkably long distances covered by deep space probes result in extremely weak downlink signals, which poses great challenges for ground measurement systems. In the current climate, improving the comprehensive utilization of downlink signal power to increase the detection distance or enhance the [...] Read more.

The remarkably long distances covered by deep space probes result in extremely weak downlink signals, which poses great challenges for ground measurement systems. In the current climate, improving the comprehensive utilization of downlink signal power to increase the detection distance or enhance the measurement accuracy is of great significance in deep space exploration. Facing this problem, we analyze the delta Differential One-way Range (ΔDOR) error budget of the X-band of the China Deep Space Network (CDSN). Then, we propose a novel interferometry method that detunes one group of DOR beacons and reuses the clock components of regenerative pseudo-code ranging signals for interferometry delay estimation. The primary advantage of this method is its ability to enhance the power utilization efficiency of downlink signals, thereby facilitating more efficient tracking and measurement without necessitating additional design requirements for deep space transponders. Finally, we analyze and verify the correctness and effectiveness of our proposed method using measured data from CDSN. Our results indicate that the proposed method can save approximately 13% of the downlink signal power and increase the detection distance by about 6.25% using typical modulation parameters. Furthermore, if the relative power of other signal components remains unchanged, the power of the DOR tone can be directly increased by more than 100%, improving the deep space exploration ability more significantly. Full article

(This article belongs to the Special Issue Digital Signal Processing, Computational Methods and Sensor Networks for Engineering Application)

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14 pages, 1320 KiB

Open AccessArticle

Reduction of Doppler and Range Ambiguity Using AES-192 Encryption-Based Pulse Coding

by Luke Kamrath, Michael Baginski and Scott Martin

Sensors 2023, 23(5), 2568; https://doi.org/10.3390/s23052568 - 25 Feb 2023

Viewed by 1118

Abstract

This research investigates the use of a Binary Phase Shift Key (BPSK) sequence derived from the 192-bit key Advanced Encryption Standard (AES-192) algorithm for radar signal modulation to mitigate Doppler and range ambiguities. The AES-192 BPSK sequence has a non-periodic nature resulting in [...] Read more.

This research investigates the use of a Binary Phase Shift Key (BPSK) sequence derived from the 192-bit key Advanced Encryption Standard (AES-192) algorithm for radar signal modulation to mitigate Doppler and range ambiguities. The AES-192 BPSK sequence has a non-periodic nature resulting in a single large and narrow main lobe in the matched filter response but also produces undesired periodic side lobes that can be mitigated through the use of a CLEAN algorithm. The performance of the AES-192 BPSK sequence is compared to an Ipatov–Barker Hybrid BPSK code, which effectively extends the maximum unambiguous range but has some limitations in terms of signal processing requirements. The AES-192 based BPSK sequence has the advantage of having no maximum unambiguous range limit, and when the pulse location within the Pulse Repetition Interval (PRI) is randomized, the upper limit on the maximum unambiguous Doppler frequency shift is greatly extended. Full article

(This article belongs to the Special Issue Digital Signal Processing, Computational Methods and Sensor Networks for Engineering Application)

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16 pages, 555 KiB

Open AccessArticle

Enhanced Root-MUSIC Algorithm Based on Matrix Reconstruction for Frequency Estimation

by Yingjie Zhu, Wuxiong Zhang, Huiyue Yi and Hui Xu

Sensors 2023, 23(4), 1829; https://doi.org/10.3390/s23041829 - 06 Feb 2023

Cited by 2 | Viewed by 1701

Abstract

In recent years, frequency-modulated continuous wave (FMCW) radar has been widely used in automatic driving, settlement monitoring and other fields. The range accuracy is determined by the estimation of the signal beat frequency. The existing algorithms are unable to distinguish between signal components [...] Read more.

In recent years, frequency-modulated continuous wave (FMCW) radar has been widely used in automatic driving, settlement monitoring and other fields. The range accuracy is determined by the estimation of the signal beat frequency. The existing algorithms are unable to distinguish between signal components with similar frequencies. To address this problem, this study proposed an enhanced root-MUSIC algorithm based on matrix reconstruction. Firstly, based on the sparsity of a singular value vector, a convex optimization problem was formulated to identify a singular value vector. Two algorithms were proposed to solve the convex optimization problem according to whether the standard deviation of noise needed to be estimated, from which an optimized singular value vector was obtained. Then, a signal matrix was reconstructed using an optimized singular value vector, and the Hankel structure of the signal matrix was restored by utilizing the properties of the Hankel matrix. Finally, the conventional root-MUSIC algorithm was utilized to estimate the signal beat frequency. The simulation results showed that the proposed algorithm improved the frequency resolution of multi-frequency signals in a noisy environment, which is beneficial to improve the multi-target range accuracy and resolution capabilities of FMCW radar. Full article

(This article belongs to the Special Issue Digital Signal Processing, Computational Methods and Sensor Networks for Engineering Application)

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16 pages, 1581 KiB

Open AccessArticle

An Efficient CRT Based Algorithm for Frequency Determination from Undersampled Real Waveform

by Yao-Wen Zhang, Xian-Feng Han and Guo-Qiang Xiao

Sensors 2023, 23(1), 452; https://doi.org/10.3390/s23010452 - 01 Jan 2023

Cited by 1 | Viewed by 1181

Abstract

The Chinese Remainder Theorem (CRT) based frequency estimation has been widely studied during the past two decades. It enables one to estimate frequencies by sub-Nyquist sampling rates, which reduces the cost of hardware in a sensor network. Several studies have been done on [...] Read more.

The Chinese Remainder Theorem (CRT) based frequency estimation has been widely studied during the past two decades. It enables one to estimate frequencies by sub-Nyquist sampling rates, which reduces the cost of hardware in a sensor network. Several studies have been done on the complex waveform; however, few works studied its applications in the real waveform case. Different from the complex waveform, existing CRT methods cannot be straightforwardly applied to handle a real waveform’s spectrum due to the spurious peaks. To tackle the ambiguity problem, in this paper, we propose the first polynomial-time closed-form Robust CRT (RCRT) for the single-tone real waveform, which can be considered as a special case of RCRT for arbitrary two numbers. The time complexity of the proposed algorithm is

O (L)

, where L is the number of samplers. Furthermore, our algorithm also matches the optimal error-tolerance bound. Full article

(This article belongs to the Special Issue Digital Signal Processing, Computational Methods and Sensor Networks for Engineering Application)

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18 pages, 4188 KiB

Open AccessArticle

A High-Accuracy, High Anti-Noise, Unbiased Frequency Estimator Based on Three CZT Coefficients for Deep Space Exploration Mission

by Weitao Lu, Lue Chen, Zhen Wang, Jianfeng Cao and Tianpeng Ren

Sensors 2022, 22(19), 7364; https://doi.org/10.3390/s22197364 - 28 Sep 2022

Viewed by 1108

Abstract

Deep space exploration navigation requires high accuracy of the Doppler measurement, which is equivalent to a frequency estimation problem. Because of the fence effect and spectrum leakage, the frequency estimation performances, which is based on the FFT spectrum methods, are significantly affected by [...] Read more.

Deep space exploration navigation requires high accuracy of the Doppler measurement, which is equivalent to a frequency estimation problem. Because of the fence effect and spectrum leakage, the frequency estimation performances, which is based on the FFT spectrum methods, are significantly affected by the signal frequency. In this paper, we propose a novel method that utilizes the mathematical relation of the three Chirp-Z Transform (CZT) coefficients around the peak spectral line. The realization, unbiased performance, and algorithm parameter setting rule of the proposed method are described and analyzed in detail. The Monte Carlo simulation results show that the proposed method has a better anti-noise and unbiased performance compared with some traditional estimator methods. Furthermore, the proposed method is utilized to process the raw data of MEX and Tianwen-1 satellites received by Chinese Deep Space Stations (CDSS). The results show that the Doppler estimation accuracy of MEX and Tianwen-1 are both about 3 millihertz (mHz) in 1-s integration, which is consistent with that of ESA/EVN/CDSN and a little better than that of the Chinese VLBI network (CVN). Generally, this proposed method can be effectively utilized to support Chinese future deep space navigation missions and radio science experiments. Full article

(This article belongs to the Special Issue Digital Signal Processing, Computational Methods and Sensor Networks for Engineering Application)

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18 pages, 4935 KiB

Open AccessArticle

Modelling and Investigation of Energy Harvesting System Utilizing Magnetically Levitated Permanent Magnet

by Joanna Bijak, Tomasz Trawiński, Marcin Szczygieł and Zygmunt Kowalik

Sensors 2022, 22(17), 6384; https://doi.org/10.3390/s22176384 - 24 Aug 2022

Cited by 4 | Viewed by 1693

Abstract

The aim of this article is mathematical modelling and investigation of chosen parameters of a small energy harvesting system designed for energy harvesting from car tire mechanical vibrations to provide power supply for various sensors, e.g., in tire pressure monitoring system. The energy [...] Read more.

The aim of this article is mathematical modelling and investigation of chosen parameters of a small energy harvesting system designed for energy harvesting from car tire mechanical vibrations to provide power supply for various sensors, e.g., in tire pressure monitoring system. The energy harvester consists of three permanent magnets inserted into a tube made from polyamide material. Comsol program has been used to calculate the force between the magnets, the stiffness of the magnetic spring, and the natural frequency of the system. MATLAB program has been used to simulate the movement of the moveable magnet to compare it with the measurements. Finally, the parameters of the mathematical model of the energy harvester were investigated and validated on a specially prepared laboratory test bench. Full article

(This article belongs to the Special Issue Digital Signal Processing, Computational Methods and Sensor Networks for Engineering Application)

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20 pages, 1090 KiB

Open AccessArticle

Data Analysis and Filter Optimization for Pulse-Amplitude Measurement: A Case Study on High-Resolution X-ray Spectroscopy

by Kasun Sameera Mannatunga, Bruno Valinoti, Werner Florian Samayoa, Maria Liz Crespo, Andres Cicuttin, Jerome Folla Kamdem, Luis Guillermo Garcia and Sergio Carrato

Sensors 2022, 22(13), 4776; https://doi.org/10.3390/s22134776 - 24 Jun 2022

Cited by 1 | Viewed by 1672

Abstract

In this study, we present a procedure to optimize a set of finite impulse response filter (FIR) coefficients for digital pulse-amplitude measurement. Such an optimized filter is designed using an adapted digital penalized least mean square (DPLMS) method. The effectiveness of the procedure [...] Read more.

In this study, we present a procedure to optimize a set of finite impulse response filter (FIR) coefficients for digital pulse-amplitude measurement. Such an optimized filter is designed using an adapted digital penalized least mean square (DPLMS) method. The effectiveness of the procedure is demonstrated using a dataset from a case study on high-resolution X-ray spectroscopy based on single-photon detection and energy measurements. The energy resolutions of the K

_{α}

and K

_{β}

lines of the Manganese energy spectrum have been improved by approximately

20 %

, compared to the reference values obtained by fitting individual photon pulses with the corresponding mathematical model. Full article

(This article belongs to the Special Issue Digital Signal Processing, Computational Methods and Sensor Networks for Engineering Application)

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21 pages, 607 KiB

Open AccessArticle

Solving the Integral Differential Equations with Delayed Argument by Using the DTM Method

by Edyta Hetmaniok, Mariusz Pleszczyński and Yasir Khan

Sensors 2022, 22(11), 4124; https://doi.org/10.3390/s22114124 - 29 May 2022

Cited by 9 | Viewed by 1402

Abstract

Recently, a lot of attention has been paid to the field of research connected with the wireless sensor network and industrial internet of things. The solutions found by theorists are next used in practice in such area as smart industries, smart devices, smart [...] Read more.

Recently, a lot of attention has been paid to the field of research connected with the wireless sensor network and industrial internet of things. The solutions found by theorists are next used in practice in such area as smart industries, smart devices, smart home, smart transportation and the like. Therefore, there is a need to look for some new techniques for solving the problems described by means of the appropriate equations, including differential equations, integral equations and integro-differential equations. The object of interests of this paper is the method dedicated for solving some integro-differential equations with a retarded (delayed) argument. The proposed procedure is based on the Taylor differential transformation which enables to transform the given integro-differential equation into a respective system of algebraic (nonlinear, very often) equations. The described method is efficient and relatively simple to use, however a high degree of generality and complexity of problems, defined by means of the discussed equations, makes impossible to obtain a general form of their solution and enforces an individual approach to each equation, which, however, does not diminish the benefits associated with its use. Full article

(This article belongs to the Special Issue Digital Signal Processing, Computational Methods and Sensor Networks for Engineering Application)

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19 pages, 2185 KiB

Open AccessArticle

Computational Methods for Parameter Identification in 2D Fractional System with Riemann–Liouville Derivative

by Rafał Brociek, Agata Wajda, Grazia Lo Sciuto, Damian Słota and Giacomo Capizzi

Sensors 2022, 22(9), 3153; https://doi.org/10.3390/s22093153 - 20 Apr 2022

Cited by 4 | Viewed by 1489

Abstract

In recent times, many different types of systems have been based on fractional derivatives. Thanks to this type of derivatives, it is possible to model certain phenomena in a more precise and desirable way. This article presents a system consisting of a two-dimensional [...] Read more.

In recent times, many different types of systems have been based on fractional derivatives. Thanks to this type of derivatives, it is possible to model certain phenomena in a more precise and desirable way. This article presents a system consisting of a two-dimensional fractional differential equation with the Riemann–Liouville derivative with a numerical algorithm for its solution. The presented algorithm uses the alternating direction implicit method (ADIM). Further, the algorithm for solving the inverse problem consisting of the determination of unknown parameters of the model is also described. For this purpose, the objective function was minimized using the ant algorithm and the Hooke–Jeeves method. Inverse problems with fractional derivatives are important in many engineering applications, such as modeling the phenomenon of anomalous diffusion, designing electrical circuits with a supercapacitor, and application of fractional-order control theory. This paper presents a numerical example illustrating the effectiveness and accuracy of the described methods. The introduction of the example made possible a comparison of the methods of searching for the minimum of the objective function. The presented algorithms can be used as a tool for parameter training in artificial neural networks. Full article

(This article belongs to the Special Issue Digital Signal Processing, Computational Methods and Sensor Networks for Engineering Application)

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