Joint angle and delay estimation of point sources

Jaafar, I.; Amara, Rim; Boujemâa, Hatem; Siala, Mohamed

doi:10.1109/icecs.2005.4633421

Cited by 6 publications

(3 citation statements)

References 7 publications

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“…In the past decades, joint angle and delay estimation (JADE) has attracted vast interests [8 -10]. In [8], the classical multiple signal classi cation (MUSIC) method was introduced, which estimates parameters via the spectral peak searching and suffers from the high computational complexity. A subspace-based approach was introduced to obtain more parameter pairs in [9].…”

Section: Introductionmentioning

confidence: 99%

Estimation of multipath parameters in wireless communications using multi-way compressive sensing

Wen

Zhang

Ben

2015

J. of Syst. Eng. Electron.

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This paper addresses the problem of joint angle and delay estimation (JADE) in a multipath communication scenario. A low-complexity multi-way compressive sensing (MCS) estimation algorithm is proposed. The received data are rstly stacked up to a trilinear tensor model. To reduce the computational complexity, three random compression matrices are individually used to reduce each tensor to a much smaller one. JADE then is linked to a low-dimensional trilinear model. Our algorithm has an estimation performance very close to that of the parallel factor analysis (PARAFAC) algorithm and automatic pairing of the two parameter sets. Compared with other methods, such as multiple signal classication (MUSIC), the estimation of signal parameters via rotational invariance techniques (ESPRIT), the MCS algorithm requires neither eigenvalue decomposition of the received signal covariance matrix nor spectral peak searching. It also does not require the channel fading information, which means the proposed algorithm is blind and robust, therefore it has a higher working ef ciency. Simulation results indicate the proposed algorithm have a bright future in wireless communications.

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Section: Introductionmentioning

confidence: 99%

Estimation of multipath parameters in wireless communications using multi-way compressive sensing

Wen

Zhang

Ben

2015

J. of Syst. Eng. Electron.

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“…Unfortunately, the computational burden of the SAGE algorithm is high due to the necessity of nonlinear and multidimensional optimization procedure. Since Swindlehurst proposed several computational efficient algorithms for the estimation of the delays of a multiray channel and solved the spatial signatures (or DOAs) as a least square problem [6], International Journal of Antennas and Propagation many algorithms which can estimate the channel parameters by a 2D searching on the DOA-delay domain or DOA-frequency domain have been proposed such as JADE-MUSIC algorithm [7], TST-MUSIC algorithm [8], FSF-MUSIC algorithm [9].…”

Section: Introductionmentioning

confidence: 99%

Channel Parameter Estimation for Scatter Cluster Model Using Modified MUSIC Algorithm

Yang

Wang

2012

International Journal of Antennas and Propagation

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Recently, the scatter cluster models which precisely evaluate the performance of the wireless communication system have been proposed in the literature. However, the conventional SAGE algorithm does not work for these scatter cluster-based models because it performs poorly when the transmit signals are highly correlated. In this paper, we estimate the time of arrival (TOA), the direction of arrival (DOA), and Doppler frequency for scatter cluster model by the modified multiple signal classification (MUSIC) algorithm. Using the space-time characteristics of the multiray channel, the proposed algorithm combines the temporal filtering techniques and the spatial smoothing techniques to isolate and estimate the incoming rays. The simulation results indicated that the proposed algorithm has lower complexity and is less time-consuming in the dense multipath environment than SAGE algorithm. Furthermore, the estimations’ performance increases with elements of receive array and samples length. Thus, the problem of the channel parameter estimation of the scatter cluster model can be effectively addressed with the proposed modified MUSIC algorithm.

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“…1. The channel model is derived from van der Veen et al (1997) and Jaafar et al (2005), and is represented by a complex channel matrix H, which contains informations about the position of objects. For convenience, we consider a single-user mode here; however, this case is without loss of generality because each user is placed in its own time slot.…”

Section: Problem Formulationmentioning

confidence: 99%

Data preprocessing for a vehicle-based localization system used in road traffic applications

Patelczyk¹,

Löffler²,

Biebl³

2016

Adv. Radio Sci.

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Abstract. This paper presents a fixed-point implementation of the preprocessing using a field programmable gate array (FPGA), which is required for a multipath joint angle and delay estimation (JADE) used in road traffic applications. This paper lays the foundation for many model-based parameter estimation methods. Here, a simulation of a vehicle-based localization system application for protecting vulnerable road users, which were equipped with appropriate transponders, is considered. For such safety critical applications, the robustness and real-time capability of the localization is particularly important. Additionally, a motivation to use a fixedpoint implementation for the data preprocessing is a limited computing power of the head unit of a vehicle. This study aims to process the raw data provided by the localization system used in this paper.The data preprocessing applied includes a wideband calibration of the physical localization system, separation of relevant information from the received sampled signal, and preparation of the incoming data via further processing. Further, a channel matrix estimation was implemented to complete the data preprocessing, which contains information on channel parameters, e.g., the positions of the objects to be located.In the presented case of a vehicle-based localization system application we assume an urban environment, in which multipath propagation occurs. Since most methods for localization are based on uncorrelated signals, this fact must be addressed. Hence, a decorrelation of incoming data stream in terms of a further localization is required. This decorrelation was accomplished by considering several snapshots in different time slots. As a final aspect of the use of fixed-point arithmetic, quantization errors are considered. In addition, the resources and runtime of the presented implementation are discussed; these factors are strongly linked to a practical implementation.

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Joint angle and delay estimation of point sources

Cited by 6 publications

References 7 publications

Estimation of multipath parameters in wireless communications using multi-way compressive sensing

Estimation of multipath parameters in wireless communications using multi-way compressive sensing

Channel Parameter Estimation for Scatter Cluster Model Using Modified MUSIC Algorithm

Data preprocessing for a vehicle-based localization system used in road traffic applications

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