of the performance of microwave absorbers [10], source location estimation [11] microwave tomography [12] and microwave near-field imaging for cancer detection [13]. In these works, probes are generally optimized and characterized to operate over a **narrow** frequency **band**. In this work, the OMS technique is chosen as a low perturbation solution to diagnose DFA calibration. The presence of variable obstacles is detected by monitoring the change in the level of the scattered power by the probe (as described in Section 3.1). Increasing the backscattering power is a key objective while keeping a low level of disturbance. In our study, the DF system has very wide **band**, to support (VHF-UHF) spectrum monitoring application. This paper proceeds as follows. In Section 2, the benefit of an in-situ monitoring system for DFA is presented. The principle of the selected approach and testbed component characterization is detailed in Section 3. The influence of obstacles near the antenna is shown in Section 4. A relation between the OMS signal level probe variations induced by the presence of the obstacle and the degradation of the performance of DF is presented in Section 5.

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To obtain the false-alarm rate and probability of detection for different threshold settings, it is necessary to know the probability density function and the corresponding cumulative distribution function of the correlator output. Since sampling or integration can be used to enhance the output signal-to-noise ratio (see section 4.5), the pdf and cdf for the summation of n independent sam ples m ust be known. As m entioned above, several authors analysed this case. Wilson and Andrews approach the problem by deriving the characteristic function and exploiting th e fact th a t the characteristic function of a sum of n independent samples is th a t for one sample raised to th e power n [Wil 79], [And 83]. Wilson derives expressions under the assumption th a t the noises a t the input of the cross correlator are uncorrelated, w hereas Andrews takes correlation into account. Both of them consider a sinusoid plus **narrow** **band** noise as input signals. Milne on the other hand only allows correlated noise at the inputs [Mil 91]. He obtains the pdf of the sum of n independent samples by repeatedly convolving the pdf of a single sample with itself. Since Milne's analysis has not been published, it is given in appendix 6. It is also shown in this appendix th a t Andrews's results, with a correction factor for the pdf, and Milne's expressions can be transformed into one another.

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Abstract . This paper researched the performance of the Capon beamformer and MUSIC algorithm using to estimate the **direction** of single **narrow**-**band** interference. The simulation was performed in the BDS (BeiDou Navigation Satellite System) B3 **band** (1268.52±10.23MHz) with four-element rectangular and linear antenna arrays. The simulation results show that the dimension of the interference **direction**-**finding** is related to the antenna array. The linear array can only estimate the elevation angle. The rectangular array can simultaneously estimate the elevation angle and azimuth. Under ideal conditions, the accuracy of both algorithms is better than 2.

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Many existing literatures describe the methods for miniaturizing a ﬁlter, such as hairpin resonant unit [5], folded stripline resonant unit [6], and spiral resonant unit [7]. These theories and methods have greatly reduced the size of a resonant unit to 1/4 wavelength or even 1/8 wavelength [8]. However, the application of these theories and methods in L-**band** cannot eﬀectively reduce the size of the resonant element. Taking advantage of the LTCC technology in a three-dimensional structure, lump-capacitor inductance is realized in the Z **direction** by means of stacking [9], thus the volume of the ﬁlter can be eﬀectively reduced, and the integrity and reliability of the LC ﬁlter are improved. Miniaturized LTCC LC ﬁlter has pushed the rapid development of civil and military electronic products in the **direction** of high reliability, miniaturization, high performance, and low cost.

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Methods: Forty-seven patients were prospectively enrolled, and magnifying NBI examinations were performed in the lesser curvature of the midbody and the greater curvature of the upper body. The marginal turbid **band** (MTB) was defined as an enclosing white turbid **band** on the epithelial surface/gyri; light blue crest (LBC), as a fine, blue-white line on the crest of the epithelial surface/gyri. Immediately after observation under magnifying endoscopy, biopsy specimens were obtained from the evaluated areas.

When the plasmonic metamaterial structures are sur- rounded by gas and liquid, a spectral shift of the reson- ance wavelength can be occurred due to the change of refractive index of environment. Thus, in practical appli- cation, **narrow** **band** absorbers are often used as bio- sensor, owing to the narrower **band** to improve the sensing performance. In designing sensors, the wave- length sensitivity (S) and the FOM are generally used for evaluating their performance, where the sensitivity and figure of merit are defined as S = Δλ/Δn, FOM = S/ FWHM respectively. The Δλ is the resonance wave- length change of reflectance spectrum, which results from the refractive index change of surrounding envir- onment, and FWHM is the full width at half maximum of the reflectance spectrum. As we all know, the higher FOM of refractive index sensor means the bio-sensor with better performance of molecule detection. Thus, it is very meaningful to design an ultra-high FOM refract- ive index sensor with a simple structure. Unfortunately, the previously reported plasmonic sensors based on metamaterial structure generally have a relatively low FOM <600 [22–39], which will severely limit their

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Traditional UVA irradiance measurement techniques either employ broadband measuring techniques, such as radiometers, or narrowband measuring techniques, such as employed in sunphotometers, spectroradiometers, Brewer spectrophotometers and **narrow** **band** filter instruments (1,3) . Radiometers measure either the unweighted UV over a certain waveband or

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Smart antennas use antenna arrays with signal processing algorithms for identifying signals spatially. The **direction** of arrival (DOA) estimation has a significant role in the implementation of a smart antenna. The conventional and super resolution methods have been used for DOA estimation applications for a long time. These methods have been quite efficient. However, some of them have computational complexities associated with them. Besides, these methods exhibit limited performance in dealing with the correlated signals. Such reasons limit their suitability for real time applications. Neural networks are non linear and use simple mathematical operators. They map the non linear behavior of smart antennas and perform DOA estimations accurately with considerable time reduction. The multi layer perceptron (MLP) based neural networks have demonstrated their capability of estimating DOAs very effectively even for correlated signals.

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of the results (S 21 curves) are shown in Fig. 3, where we can see that f 0 changes significantly with CSRR length L S . In the stop **band** near resonant frequency, CSRR and microstrip have great mutual coupling and good inhibition achieved. The rejection level is 15 dB, while on the other **band**, they have weak coupling. We use interpolation method to extract the relationship between center frequency f 0 (in GHz) and

In the design of the **narrow** **band** antenna, developing a rational model for the antenna is one of the most common and practical way to characterize the electromagnetic characteristics of the antenna [2]. In general, the rational model is closely related to the physics and geometry of the antenna, which can provide a good reference for the design of the antenna through simulating the parameters of the rational model [3]. There are two basic requirements to propose the rational model [4].The first one is the impedance requirement: the input impedance Z in and admittances Y in of the rational model should

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This paper describes an experiment which aims to examine the effectiveness and efficiency of a Virtual Reality Modelling Language (VRML) building model compared with equivalent architectural plans, for **direction** **finding** purposes. The effectiveness and efficiency issues being primarily investigated were number of tasks completed overall and task completion times. The experiment involved a series of tasks where participants had to find a number of locations/objects in a building unknown to them at the outset of the experiment. Statistically significant results are presented for the benefit of the research community, law enforcement officers and fire fighters where it is clear that in this context, the VRML model led to better task completions than the equivalent architectural plans. Regarding the task completion times, no statistical significance was found. Given the current climate of security issues and terrorist threats, it is important that law enforcement officers have at their disposal the best information possible regarding the layout of a building, whilst keeping costs down. This also applies to fire fighters when rescuing victims. This experiment has shown that a VRML model leads to better task completions in **direction** **finding**.

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After adopting the open circuit coupling structure at the outer stub line which is a capacitive load, the harmonic suppression ability of the proposed filter is improved and the first tr[r]

The incorporation of low concentrations (1%) of nitrogen-atoms in III-V semiconductor compounds acts to modify the electronic **band** structure of the host crystal, thus enabling **band** structure engineering and a fine tuning of fun- damental electronic properties, such as the **band** gap energy. 1,2 An additional attractiveness of this class of com- pounds is the possibility of using post-growth hydrogenation, combined with electron beam lithography and masking 3 or laser writing, 4 to create distinct, tailor-made light emitting regions, 3,4 all integrated onto a single substrate. These effects rely on the ability of hydrogen to modulate the material opti- cal properties by passivating the electronic activity of nitro- gen through the formation of di-hydrogen N-H 2 complexes. 5

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For **direction** ﬁnding of MIMO radar with uniform linear array (ULA), many methods have been proposed [10–14]. Reduced-dimension MUSIC for angle estimation has been derived in [10], which only requires one-dimensional search and can save computational time. Unfortunately, the algorithm will fail to work in the presence of array gain-phase error. It is proved in [11] that the ESPRIT algorithm exploits invariance properties of both transmit and receive ULAs, and can estimate the transmit and receive angles of MIMO radar eﬃciently. However, the algorithm estimates the two angles separately in each dimension and requires an additional pairing procedure. The ESPRIT method without pairing is proposed in [12], and by doing so, the transmit and receive angles can be paired automatically. Uniform circular array (UCA) can provide both azimuth and elevation angles, which are attractive in many practical applications [15–17]. Based on the MIMO radar with transmit UCA, the three-dimensional (3-D) coordinates of targets are estimated [18].

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In this paper, we propose a new extended cyclic **direction** **finding** method that allows to select desired signals and to ig- nore interferences, by exploiting the cyclostationarity prop- erty of the signals of interest (SOI). The proposed method is inspired from the extended root-MUSIC method [4], and then is restricted to linear uniformly spaced arrays. But it has the distinct advantage over [3] in that it does not require a search over parameter space. Instead, our algorithm here

1) **Finding** a region of interest: First, we have to find a region of interest (ROI). This is done in a two step procedure: based on a simple thresholding, we identify the upper left and the lower right corner of the non-black part of the image and retrieve a rough region of interest. Since the first step sometimes still yields a thin black rim around the image, we additionally extract line segments associated with particular bins for horizontal and vertical lines in a Hough transform [13]. These extracted lines can then be employed to refine the ROI further and remove the leftover thin black rim. The final region of interest is shown in Figure 3 (a) and (b).

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Abstract. During the multi-station **direction** **finding** cross positioning, instable or divergent positioning evaluation result, even invalid situation will occur caused by unreasonable sensor allocation, and analyzes the causes of ill-condition in traditional localization algorithm Therefore, this paper puts forward a kind of stable positioning method based on singular value decomposition modification. The method doesn’t require the station allocation greatly and could consider the resolution and variance assessed by positioning parameter effectively. It realizes effective inhibition to the random observation noise in the observation equation and has better engineering application value. The value simulation result indicates the positioning result is more precise and stable than traditional calculating method.

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This algorithm can be applied to the localization of the sources when the spatial-spectrum of the noise or the spatial correlation function between sensors is known. The obtained results show that the proposed algorithm improves the **direction** estimates compared to those given by the MUSIC algorithm without preprocessing. Several applications on synthetic data and experiment have been presented to show the limits of these estimators according to the signal-to- noise ratio, the spatial correlation length of the noise, the number of sources, and the number of sensors of the array. The motivation of this work is to reduce the eﬀect of the additive spatially correlated noise for estimating the DOA of the sources.

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considered as beneﬁcial for using in nonlinear harvesters. A rational behind this is that, if the frequency is varied in some range, then an integral response of nonlin- ear system exceeds the **narrow**-**band** response of the corresponding linear harvester. However, this conclusion only holds true if the system stays on the upper branch of the response, otherwise the integral response of the lower branch is signiﬁcantly less than the response for linear case. Thus, stability of the upper branch is important and it has to be taken into account for an eﬃcient harvester design. The stability can be assessed via the consideration of an additional stochastic term in (2.1) and by nonlocal stability analysis (see for example Ref. 15). Majority of the research articles devoted to energy harvesting has so far failed to consider the stability is- sue. It is particularly important as the presence of additional perturbations can easily lead to a switch between the upper and lower branches of the resonant curve and, therefore, a procedure for recovering the high amplitude solution needs to be implemented.

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The noise factor F is defined as the ratio of the total output noise power in the amplifier load to the noise power at the output due to the thermal noise of the source resistance... The[r]

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