In-band spectra and filter shape monitoring using high-resolution swept coherent detection
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In this paper, a novel in-band optical spectra and filter shape monitoring technique is experimentally demonstrated. Based on swept coherent detection, the proposed technique simultaneously measures the signal and ASE spectra by adjusting the polarization states of the signal and local oscillator. In our experiment, a high resolution of 0.002 nm is achieved.Keywords:
SIGNAL (programming language)
Detection theory
Matched filter
The extended optical correlator system is a three-lens coherent correlator with the three separated planes available for spatial filtering of signals. The preprocessing of signals in two separated planes is also separated from the matched filtering. A typical preprocessing procedure is presented. Usefulness of a special type of matched filter referred to as the quasi phase-only filter is also discussed.
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The detection of binary antipodal signals in the presence of white Gaussian noise is considered. The classical error probabilities, using ideal matched-filter detection for the complete signal waveform, are compared with those where hard decisions are made on subsections of the waveform. It is shown that a penalty of about 2 dB arises from this technique.
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Gaussian Noise
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We consider the generic problem of detecting a transmitted signal when one of M known signals is transmitted. Instead of using a classical matched filter (MF) detector, matched to the transmitted signals, we propose using an orthogonal matched filter (OMF) detector, which is matched to a set of orthogonal signals that are closest in a least-squares sense to the transmitted signals. We show that this approach is equivalent to optimally whitening the output of the MF demodulator, and then basing the detection on the whitened output. We provide simulation results which suggest that, in many cases, the OMF detector outperforms the MF detector.
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Target detection is a probabilistic idea; noise and clutter prevent us from being certain to find the targets we are looking for, and will normally present us with plenty of 'targets' we are not looking for. We can only define the probabilities of detection and of false alarm that we are prepared to live with. These determine the signal-to-noise ratio that is required for detection. Optimal detection performance is achieved by maximizing the SNR at the output of the receiver. The receiver that does this uses the correlation or matched filter principle. As long as a matched filter is being used, the form of the transmitted pulse is irrelevant for detection purposes. All that matters is the ratio of the signal energy to the noise power per unit bandwidth on input to the receiver. By developing expressions for the PDFs of signal plus noise and noise only, relatively straightforward calculations of detection and false-alarm probabilities can be carried out for single pulses. These become more complicated when fluctuating targets and multiple pulses need to be considered, so that graphical or numerical techniques are needed.
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In order to explore the effect of local oscillator optical power on the signal-to-noise ratio (SNR) of the system under the balanced detection method and the traditional single-channel detection mode in the laser coherent detection system. The numerical simulation analysis of the SNR of the coherent detection system is realized by using the local oscillator power.The self-built laser coherent detection platform is used to explore the influence of the local oscillator power on the system measurement range and SNR in the single-channel detection and dual-channel balance detection under the balanced detection mode. The results showed that: in coherent detection systems, balanced detection has certain advantages over single-channel detection. After calculation, in the detection range of 3km, the measured SNR in the balanced detection mode is higher than the single-channel detection SNR by 2.1.This conclusion has certain reference significance for improving the detection effect of the coherent detection system.
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The best signal and worst jamming are derived for a detection system which uses a matched-filter receiver. The penalty for deviation from the best signal is determined.
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Detection theory
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From the purpose of accuracy and convenience a new filter function is used to make optical matched filters in practical optical pattern recognition system by adopting Lohmann''s and Lee Waihon''s holography. These filters can reduce the halfwidth ofcorrelation peak improve the SNR and discrimination performance in correlation plane.
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Matched filter
Optical correlation
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Matched filter
Detection theory
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This chapter evaluates the detection and false-alarm characteristics for the reception of single and multiple pulses using coherent and noncoherent processing techniques. It examines the statistical performance for coherent pulse integration and detection. Coherent detection involves the matched filter detection of a single pulse. In this situation, the matched filter performs a coherent integration and a decision regarding the presence or absence of the pulse is based upon the signal-to-noise ratio (SNR) of the optimally sampled matched filter output. The coherent detection performance involves two detection hypotheses: noise only and signal plus noise. The chapter also examines noncoherent detection using the square-law and linear detectors. In the chapter, the detection probability is evaluated for the chi-square probability distribution function given the degrees of freedom (2WT), the desired SNR (γo) at the detector output, and the false-alarm probability (Pfa).
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False alarm
Detection theory
Statistical power
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This paper reviews two streams of development, from the 1940's to the present, in signal detection theory: the structure of the likelihood ratio for detecting signals in noise and the role of dynamic optimization in detection problems involving either very large signal sets or the joint optimization of observation time and performance. This treatment deals exclusively with basic results developed for the situation in which the observations are modeled as continuous-time stochastic processes. The mathematics and intuition behind such developments as the matched filter, the RAKE receiver, the estimator-correlator, maximum-likelihood sequence detectors, multiuser detectors, sequential probability ratio tests, and cumulative-sum quickest detectors, are described.
Detection theory
Matched filter
Rake
Intuition
Filtering theory
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