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Traditional passive radar systems with a noisy reference signal use the cross-correlation statistic for detection. However, owing to the composite nature of this hypothesis testing problem, no claims can be made about the optimality of this detector. In this paper, we consider digital illuminators such that the transmitted signal in a processing interval is a weighted periodic summation of several...
Woodward's ambiguity function, introduced in the literature in the mid-20th century, has been a staple topic in the study of radar performance. There exists an inherent trade-off in the ability of a signal to accurately measure both the range and velocity of a target. Woodward's ambiguity function measures this uncertainty for narrowband RF signals for monostatic radar. Despite its popularity and...
Methods for measuring the impulse response of a linear transmission system and system identification algorithms in general must be robust against noise in the measured system response. To handle the noise it is of great advantage to know the instantaneous signal-to-noise ratio (SNR), especially in situations with changing noise conditions. In this paper we present a new approach for estimating the...
In this paper, we present a method for estimating the signal sources steering vector using an arbitrary planar array with omnidirectional elements. The proposed method improves the initial estimation of the signal steering vector in two steps. In the first step of this algorithm we minimize of the distance between the steering vector and the signal subspace. The second step improves the estimation...
In this paper, a new multitarget tracking approach is proposed. In the proposed approach, a non-iterative fuzzy clustering means algorithm is used to generate the association measures between the received measurements and the targets. Measurements-to-tracks associations are computed jointly across all targets and all validated measurements using the non- iterative fuzzy clustering means algorithm...
Accurate heart rate estimation is a fundamental process when analysing phonocardiograms (PCGs). While this is trivial in noise-free recordings, it becomes a difficult task in PCGs corrupted by various noise sources. While numerous PCG-based heart rate estimation techniques have been explored in the literature, no comparison between these techniques has been performed to identify the best-performing...
The conventional linear prediction (LP) analysis is known to suffer from problems that it is sensitive to additive noise. In this paper a new approach for LP analysis of crosscorrelation sequence between speech signal and its zero-crossing wave has been presented. Simulation results show that the proposed method is capable of performing the speech analysis under a white noisy environment.
The channel capacity of indoor 60 GHz radio is studied in this work from the diversity and the directivity viewpoints of multiple input multiple output (MIMO) wireless systems. To characterize the diversity and directivity (DnD) tradeoff of using planar antenna arrays (PAA) in indoor 60 GHz channels, a hybrid architecture for dual-polarized PAA (DP-PAA) is employed to exploit the potential advantages...
In this paper a phase detection method for fault diagnosis of the induction motors has been presented. The proposed method has a powerful environmental noise suppression capability. It has been shown in literature that the performance of the previously used fault detection method (instantaneous power analysis) was affected by the environmental noise, switching disturbances and other low order harmonics...
Unsupervised feature selection is an important issue for high dimensional dataset analysis. However popular methods are susceptible to noisy instances (observations) or noisy features. We propose a noise-resistant feature selection algorithm by capturing multi-perspective correlations. Our proposed approach, called Noise-Resistant Unsupervised Feature Selection (NRFS), is based on multi-perspective...
The Electroencephalogram (EEG) is often contaminated by muscle artifacts. EEG is a widely used recording technique for the study of many brain related diseases such as epilepsy. The detection and removal of muscle artifacts from the EEG signal poses a real challenge and is crucial for the reliable interpretation of EEG-based quantitative measures. In this paper, an automatic method for detection and...
In the process of distant target imaging by optical telescope, large aperture mirrors with high precision is needed to collect the light field of target, the result is affected by atmospheric turbulence and aberration seriously, and lensless imaging is a new way which can reduce imaging equipment's complexity and accuracy requirements. In this paper, we put forward a new lensless imaging method on...
Terrain-Relative Navigation (TRN) is a technique for localizing a vehicle in GPS-denied environments. TRN augments a dead-reckoned solution with continuous position fixes based on correlations with a pre-stored map. In underwater applications TRN accuracy on the order of 3m has been demonstrated, however convergence to incorrect solutions has been observed when operating for extended periods over...
This paper focuses on phase noise measurement techniques and comments about the dangers of using cross-correlation techniques for measuring Phase noise below kT. This discussion is important for research, demonstrated on 1GHz VCSO, and validated using different measurement equipments.
We present the analysis of different schemes for simultaneous acquisition of an electric signal. The results can be used to monitor-based source-drift correction for optical metrology. The degree of correlation between the measured signals is expected to directly influence on the calibration uncertainty in applications in Radiometry.
A new classification framework is proposed for noise invariant hand-written digit recognition, which is based on the Turbo decoding technique and the Viterbi algorithm. Specifically, labeled training digit images are transformed into a two-dimensionally correlated Markov Chain Model (MCM). In order to increase the discriminant function of MCMs, a novel sequence learning algorithm is proposed to obtain...
This paper presents a novel and efficient audio signal recognition algorithm with limited computational complexity. As the audio recognition system will be used in real world environment where background noises are high, conventional speech recognition techniques are not directly applicable, since they have a poor performance in these environments. So here, we introduce a new audio recognition algorithm...
Since 2010 we have been developing a quantum-voltage-calibrated Johnson noise thermometer at NIM to measure the Boltzmann constant k. With recent improvements in grounding and shielding of the electronics, and matching of the noise sources and transmission lines, the effects of electromagnetic interference and variations of fitting parameters with different bandwidths were greatly reduced. By combining...
Noise Radar Technology (NRT) is nowadays a promising tool in radar systems. It is based on the transmission of waveforms composed of many noisy samples, which behave as LPI (Low Probability of Intercept) and antispoofing signals. Each noisy sequence is theoretically uncorrelated with the others. In the paper we propose a scheme to generate a “tailored” pseudo-random sequences (limited in amplitude)...
In this article, we present a novel non-local video denoising scheme using low-rank representation and total variation regularization. The proposed scheme attempts to make full use of the intrinsic properties that the grouping similar patches not only lie in a low-rank subspace but are also sparse in total variation (TV) domain. For a group of similar patches, we formulate video denoising problem...
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