In this paper, we develop a scheme to partition a one- or multi-dimensional consecutive integer number set into multiple identical, possibly rotated, subsets. The proposed technique first exploits one-dimensional nest...
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ISBN:
(纸本)9798350344820;9798350344813
In this paper, we develop a scheme to partition a one- or multi-dimensional consecutive integer number set into multiple identical, possibly rotated, subsets. The proposed technique first exploits one-dimensional nested subsets, and the results are extended to achieve two- and multi-subset partitioning as well as in two- and multi-dimensional spaces. The number of consecutive lags in each case is examined. The results are useful to various sensing and communication applications, and sparse step-frequency waveform design for range estimation in automotive radar is demonstrated as an example.
Source localization from raw array data by reparameterizing the array steering vector by the source position is a fundamental principle of direct position determination (DPD). In this paper, we propose a DPD method to...
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ISBN:
(纸本)9798350344820;9798350344813
Source localization from raw array data by reparameterizing the array steering vector by the source position is a fundamental principle of direct position determination (DPD). In this paper, we propose a DPD method to estimate the position of locally scattered sources using an unsynchronized arraysensor network. Here, we use the well-known generalized array manifold (GAM) model which approximates the steering vector using its first-order gradient in order to characterize the local scattering effect. The proposed method is compared with the conventional two-stage bearings-only localization (BOL) approach. Simulation results reveal that the proposed DPD position estimates asymptotically attain the derived Cramier-Rao Bound (CRB) for high SNR values and an improved localization accuracy is achieved by exploiting the local scattering parameters in the localization.
In this paper, we propose high-resolution target direction-of-arrival (DOA) estimation using frequency-switching sparse arrays which implement multi-frequency sparse arrays in a low-complexity manner. Unlike multi-fre...
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ISBN:
(纸本)9798350344820;9798350344813
In this paper, we propose high-resolution target direction-of-arrival (DOA) estimation using frequency-switching sparse arrays which implement multi-frequency sparse arrays in a low-complexity manner. Unlike multi-frequency sparse arrays which require processing of wideband signals comprising multiple frequency components, the proposed frequency-switching sparse arrays only need to process a single-frequency component at any time instant, thereby eliminating such hurdles and significantly reducing the system complexity. A frequency-switching sparse array achieves the same number of degrees-of-freedom as a multi-frequency counterpart with comparable DOA estimation performance. Numerical results on the DOA estimation performance and Cramer-Rao bounds are provided to illustrate the effectiveness of the proposed frequency-switching sparse arrays.
The proceedings contain 134 papers. The topics discussed include: decentralized direction finding using Lanczos method;on MSE performance of time-reversal MUSIC;optimal virtual array length under position imperfection...
ISBN:
(纸本)9781479914814
The proceedings contain 134 papers. The topics discussed include: decentralized direction finding using Lanczos method;on MSE performance of time-reversal MUSIC;optimal virtual array length under position imperfections;direction finding and array calibration based on sparse reconstruction in partly calibrated arrays;analytical esprit-based performance study: what can we gain from non-circular sources?;direction of arrival estimation of harmonic signal using single moving sensor;network design via modular set function optimization in localization problems;cooperative simultaneous localization and synchronization: toward a low-cost hardware implementation;preprocessing algorithm for source localisation in a multipath environment;a weighted KNN epipolar geometry-based approach for vision-based indoor localization using smartphone cameras;and improving the projection method for TOA source localization in the presence of sensor position errors.
Graph learning has been widely used in many fields to study the relationships between different entities in a dataset. We present an optimization framework based on the proximal alternating direction method of multipl...
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ISBN:
(纸本)9798350344820;9798350344813
Graph learning has been widely used in many fields to study the relationships between different entities in a dataset. We present an optimization framework based on the proximal alternating direction method of multipliers (pADMM) for learning general signed graphs from smooth signals. We show that our proposed pADMM enjoys global convergence and a local linear convergence rate. Then, we demonstrate the effectiveness of the proposed framework through numerical experiments on signed graphs. Our proposed framework provides a promising approach for learning general signed graphs from smooth signals and can be a valuable tool for data analysis and decision-making in various fields.
In this paper, we explore the use of large-scale sparse arrays for pilot placement in pilot-based sensing within integrated sensing and communication (ISAC) systems. Unlike conventional regular pilot placement method,...
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ISBN:
(纸本)9798350344820;9798350344813
In this paper, we explore the use of large-scale sparse arrays for pilot placement in pilot-based sensing within integrated sensing and communication (ISAC) systems. Unlike conventional regular pilot placement method, sparse placement offers a significant reduction in overhead while maintaining high sensing performance. We present a novel large-scale sparse array construction method by introducing a multi-tier array structure. Using the proposed method, the design of large-scale sparse arrays can be simplified into several smaller-sized array design problems, significantly reducing computational complexity and storage requirements. Numerical examples demonstrate the effectiveness of the proposed method for low-overhead sensing pilot placement design, which is applicable in future 6G applications.
This paper addresses the problem of calibration for antenna arrays with multi-port polarimetric elements. Model-based arraysignalprocessing techniques require an accurate model of the complex array response and mode...
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ISBN:
(纸本)9798350344820;9798350344813
This paper addresses the problem of calibration for antenna arrays with multi-port polarimetric elements. Model-based arraysignalprocessing techniques require an accurate model of the complex array response and model errors can, for example, cause significant systematic direction finding errors. Modeling the response of polarimetric antenna arrays can be particularly challenging due to cross-polarization and mutual coupling effects in the multi-port antenna elements. This work proposes a new calibration technique for polarimetric antenna arrays using neural networks that learn any mismatches between the modeled and the actual array response. The technique is evaluated based on the measured response of a five-element dual-polarized antenna array and outperforms conventional calibration techniques like mutual coupling calibration or local polynomial approximation. Its performance is studied exemplarily for the direction finding problem.
Spatial frequency estimation from a superposition of impinging waveforms in the presence of noise is important in many applications. While subspace-based methods offer high-resolution parameter estimation at a low com...
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ISBN:
(纸本)9798350344820;9798350344813
Spatial frequency estimation from a superposition of impinging waveforms in the presence of noise is important in many applications. While subspace-based methods offer high-resolution parameter estimation at a low computational cost, they heavily rely on precise array calibration with a synchronized clock, posing challenges for large distributed antenna arrays. In this study, we focus on direction-of-arrival (DoA) estimation within sparse partly calibrated rectangular arrays. These arrays consist of multiple perfectly calibrated subarrays with unknown phase-offsets among them. We present a gridless sparse formulation for DoA estimation leveraging the multiple shift-invariance properties in the partly calibrated array. Additionally, an efficient blind calibration technique is proposed based on semidefinite relaxation to estimate the intersubarray phase-offsets accurately.
We describe the problem of joint sensing and communications (JSAC) using an antenna array where some antennas are used for sensing and some others for communications. The problem is to jointly optimize the sensing and...
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ISBN:
(纸本)9798350344820;9798350344813
We describe the problem of joint sensing and communications (JSAC) using an antenna array where some antennas are used for sensing and some others for communications. The problem is to jointly optimize the sensing and communications performance at the receive side through respectively the CramerRao bound (CRB) on the source angles and the variance of the sources after applying a minimum variance distortionless response (MVDR) beamformer. Both criteria are derived under a two-source scenario and optimized for any position of the two sources. Here one of the sources is considered the source of interest, while the other one models the interference. The performance criteria for sensing and communications are mathematically similar and depend only on the angular difference between the two sources. As a result, they can be elegantly combined and jointly optimized. Our findings are corroborated by simulations under different parameter settings.
In this paper, we perform joint antenna selection and transmit pre-coder design for integrated sensing and communication (ISAC) systems to meet signal-to-interference-plus-noise-ratio (SINR) requirements at the users ...
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ISBN:
(纸本)9798350344820;9798350344813
In this paper, we perform joint antenna selection and transmit pre-coder design for integrated sensing and communication (ISAC) systems to meet signal-to-interference-plus-noise-ratio (SINR) requirements at the users while being capable of identifying, i.e., estimating the direction of arrivals (DoAs), of certain number of sources. We first present a sufficient condition to ensure certain identifiability. Next, through a series of relaxations, we obtain a convex approximation to the combinatorial antenna selection and precoding problem, which we solve using off-the-shelf solvers. The proposed method offers comparable performance to ISAC systems with optimal antenna selection obtained through exhaustive search while significantly out-performing ISAC systems with arbitrarily selected active antennas.
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