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Identifying the most recent heavy hitters, i.e., finding the items with the highest appearances in a high speed data stream is a fundamental problem in real-time stream processing. The requirement of real-time stream applications raises significant challenges to this problem in terms of the processing latency, the space usage and the precision. Traditional schemes leverage the sliding windows based...
The DOA estimation problem for wideband signals has attracted much attention in the past years, and how to utilize and derive the common DOA information among frequency bins is the essential question. We address the wideband DOA estimation problem in this paper, and to solve this problem we propose a joint sparse Bayesian learning algorithm based on the sparse signal representation (SSR) of the covariance...
This paper introduces the basic theory and method of compressed sensing, and its application in DOA estimation. The theory uses a new sampling method through sparse sampling and reconstruction of the signal to break through the limitation of the Nyquist sampling theorem, effectively solving the inherent shortcomings of classic spatial spectrum estimation algorithms.
The speed of the target can be estimated by the sound pressure cross-correlation of the line spectrum of the moving target at different time intervals. However, a slight deviation of the line spectrum has a significant influence on the estimated result. In this paper this phenomenon is analyzed from the theory, then the speed of the target is estimated when the line spectrum is biased. Experimental...
As the complexity of the ocean environment, shape of towed array changes with time and space, so the accurate measurement shape of towed array is the key to improve the performance of signal processing. To solve this problem this paper proposes an estimation method based on genetic algorithm, firstly, established the objective function according to a known distance and azimuth of the target by beam...
SAR Tomography (TomoSAR) regards multi-baseline observation data as array observation data and realizes three-dimensional imaging by applying direction of arrival (DOA) estimation processing. To improve angular resolution of the TomoSAR with suppressing ambiguity, many repeat-pass data are required. However, it is often difficult to increase the number of data because of the cost. In this paper, we...
In this paper, we consider the direction-of-arrivals (DOAs) estimation of coherent narrowband signals impinging on an arbitrary linear array in a computational efficient way. A new interpolation transform based modified Capon beam-forming method is proposed without eigendecomposition, where the arbitrary linear array is transformed to a virtual uniform linear array (ULA) by utilizing the interpolation...
Co-prime arrays and samplers are popular sub-Nyquist schemes for estimating second order statistics at the Nyquist rate. This paper focuses on the perturbations in the array locations or sampling times, and analyzes its effect on the difference set. Based on this analysis we propose a method to estimate the autocorrelation which makes best use of the sampled data in order to improve the estimation...
In order to solve the coherent problem of Orthogonally Matched(OMP) Pursuit algorithm in sparse reconstruction, the feature vector corresponding to large eigenvalue of SVD is constructed by using received data, and two improved methods are proposed. Both methods reconstruct the angle through the feature vector, and can reconstruct the angle information accurately without knowing the number of the...
In this paper, we propose a novel array interpolation method in logarithmic domain for enhanced direction of arrival (DOA) estimation. Array interpolation techniques are broadly utilized in the DOA estimation for achieving better angular resolution. Generally, to generate interpolated array elements from original array elements, the method of linear least squares (LLS) has been used. When we use the...
Per-flow counting for big network data streams is a fundamental problem in various network applications such as traffic monitoring, load balancing, capacity planning, etc. Traditional research focused on designing compact data structures to estimate flow sizes from the beginning of the data stream (i.e., landmark window model). However, for many applications, the most recent elements of a stream are...
The estimator bank approach allows improving the performance of direction of arrival (DOA) estimation in the area of low signal-to-noise ratio. In the paper, the estimator bank is formed from the modified Beamspace Root-MUSIC estimator using resampling by adding pseudo-noise. The illumination of outlying roots of the modified beamspace Root-MUSIC polynomial is used instead of elimination of entire...
For critical aerospace applications that experience a high intensity of single event upsets, the cache of a processor has to be protected against soft errors. This poses a challenge for cache design, since implemented redundancy causes timing and performance degradation of a processor. Sound design decisions should be made based on evaluations at every design stage. In this paper we present a platform-oriented...
Static timing analysis is crucial for design of realtime systems. While the worst-case execution time of a task is typically computed or measured in a single task environment, the presence of caches imposes additional cache related preemption delay (CRPD) cost to the lower priority tasks in a preemptive multi-tasking system. In this work, we show that existing instruction CRPD analysis techniques...
Subspace techniques are widely used for direction of arrival (DOA) problems in telecommunications and position location applications for estimating the location of sources from where the signal is originated. This source estimation problem is analogues to the source estimation problem in EEG signal processing commonly termed as EEG inverse problem. The EEG inverse problem goes for estimation of active...
Location prevails as a piece of crucial information for decision-making processes. Whereas positioning in outdoor environments can be mainly attributed to Global Navigation Satellite Systems, no single technology can be appointed for accurate indoor localization. Many approaches exist, mostly relying on line-of-sight propagation from a mobile node to multiple anchor nodes. These solutions not only...
In this paper, a new algorithm to suppress the interferences for Direction-of-Arrival(DOA) estimation is presented. The method is based on the property of the noise subspace invariant to power of emitters. With theoretical analysis and computer simulations, it is shown that the proposed method has a good performance on signal DOA estimation under disturbances.
Cumulative distribution functions (CDFs) for multiple-input-multiple-output (MIMO) capacities are computed for flat-fading indoor channels at 5.8 GHz. These CDFs are based on two measured channels and on reconstructions of the MIMO channels from path parameters that are estimated based on measured data. The measured data was obtained using the stepped-frequency method of channel sounding in combination...
This paper deals with the near-field DOA-Matrix method for source localization using a uniform linear array antenna. In general, the mutual coupling between array elements degrades the DOA estimation accuracy. In this paper, we investigate the influence of mutual coupling in source localization using the near-field DOA-Matrix method and the improved method.
Khatri-Rao (KR) product increases the number of elements virtually and enables to estimate more incoming waves in direction-of-arrival (DOA) estimation using array antenna. The DOA estimation with the KR scheme, however, makes the estimation difficult because the scheme makes the data coherent. The sparse signal reconstruction is a method realizing the DOA estimation regardless of the signal correlation...
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