Performance of homodyne detection of binary PSK optical signals

This study evaluates the performance of an optical receiver for binary phase shift keyed (BPSK) signals in the presence of noise originating from the photodetectors and the phase fluctuations of the optical sources. Analysis of the homodyne detection process shows that the performance is degraded by two effects: One due to the phase error fluctuations of the recovered carrier and the other due to reduction of the energy per bit available for data recovery. The resulting power penalty can be minimized by dividing in an optimal way the received optical signal between the carrier recovery and the data recovery circuits of the receiver. The minimum penalty thus obtained depends on the 3-dB linewidth and on the transmission rate. For example, a penalty of 0.5 dB, relative to the quantum limit of 9 photon bit needed to achieve a BER of 10^-9, imposes a minimum transmission rate of about 180 Gbit/s when the optical source has a 3-dB linewidth of 20 MHz.     

Differential detection algorithms for MSK signals over AWGN andfrequency-flat Rayleigh fading channels

Novel symbol-by-symbol differential detection algorithms are proposed for minimum-shift keying signals transmitted over additive white Gaussian noise and frequency-flat Rayleigh fading channels. They are derived as approximations to the maximum likelihood noncoherent detection strategy. Their error performance is assessed by computer simulation and is compared with that of other noncoherent detectors. It is shown that, with fading channels, the new algorithms outperform the traditional methods     

Synchronization algorithms for UWB signals

This paper is concerned with timing recovery for ultra-wideband communication systems operating in a dense multipath environment. Two timing algorithms are proposed that exploit the samples of the received signal to estimate the start of the individual frames with respect to the receiver's clock (frame timing) and the location of the first frame in each symbol (symbol timing). Channel estimation comes out as a by-product and can be used for coherent matched filter detection. The proposed algorithms require sampling rates on the order of the inverse of the pulse duration. Their performance is assessed by simulating the operation of coherent and differential detectors. Their sensitivity to the sampling rate is discussed, and the effects of the multiple access interference are evaluated.     

复合高斯杂波环境中分布性目标相干雷达恒虚警检测算法研究

本文研究了在未知统计特性的复合高斯杂波环境中对分布性目标检测的问题。利用Toeplitz矩阵的次对称性提出了一种新的杂波协方差矩阵结构的估计方法,并用此估计方法来实现基于广义似然比检验的恒虚警检测算法。该算法能够在不需要杂波功率谱密度对称的情况下作到对杂波的结构分量和协方差矩阵都有恒虚警的性质,而且该实现方法的检测性能优于先前提出的实现方法。     

The detection of chirped radar signals by means of electron spin echoes

The application of the electron spin echo phenomenon to the detection of chirped microwave pulses is considered. The attainable time resolution is determined by the width of the paramagnetic resonance line, and the length of the received waveform is limited by the phase memory time of the spin packets in the active material. Pulse compressions of 1000:1 appear to be feasible. A typical device of this kind would require to be operated at liquid helium temperatures. It could be adapted so that in itself it provided maser amplification of the compressed pulses.     

Performance of spatial smoothing algorithms for radar signaturemodelling

In the area of radar signature modelling, subspace-based methods have recently become very popular. To model radar signals using subspace-based methods, spatial-smoothing preprocessing (SSP) is essential to estimate the covariance matrix of the received signals. Here, the performances of two typical SSP techniques are compared in the context of radar signature modelling     

Combining algorithms in automatic detection of QRS complexes in ECG signals.

QRS complex and specifically R-Peak detection is the crucial first step in every automatic electrocardiogram analysis. Much work has been carried out in this field, using various methods ranging from filtering and threshold methods, through wavelet methods, to neural networks and others. Performance is generally good, but each method has situations where it fails. In this paper, we suggest an approach to automatically combine different QRS complex detection algorithms, here the Pan-Tompkins and wavelet algorithms, to benefit from the strengths of both methods. In particular, we introduce parameters allowing to balance the contribution of the individual algorithms; these parameters are estimated in a data-driven way. Experimental results and analysis are provided on the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Arrhythmia Database. We show that our combination approach outperforms both individual algorithms.     

CFAR detection for multistatic radar

In this paper a multistatic radar system with n transmitters and one receiver is considered and several constant false alarm rate (CFAR) algorithms for detection are introduced. The decision statistics of the proposed detectors are the sum of the n largest returning signals in an array of N+n range cells. It is shown that the proposed decision statistic satisfies the CFAR condition and it is justified that the sum of the largest returning signals is the optimal statistic. The proposed CFAR detectors are simulated both in homogenous and non-homogenous backgrounds and their performances are compared with the performance of a monostatic radar of higher power. It is shown that a multistatic radar outperforms a monostatic radar under equal transmit power condition.     

On quantizers for DPCM coding of picture signals

A measure of picture quality for simple element, differentially coded pictures is developed based on certain subjective tests. The measure weights the quantization noise according to its visibility. It is shown that the measure correlates well with the picture quality determined on a standard impairment scale. Optimization of DPCM quantizers is done for this and for the mean-square measure of picture quality. Performance of the following types of quantizers is evaluated in terms of entropy of the quantized output and the picture quality: a) minimum mean-square error quantizers with a fixed number of levels, b) minimum mean-square error quantizers with fixed entropy, c) minimum mean-square subjective distortion quantizers with a fixed number of levels, d) minimum mean-square subjective distortion quantizers with fixed entropy, and e) uniform quantizers. It is concluded that for a fixed number of levels and a fixed word-length coding of the quantizer outputs, the quantizers in c) outperform those in a); and with variable length coding, the quantizers in d) perform better than all of the other quantizers having the same entropy. The sensitivity of the approach to variation of picture content is also investigated.     

Two-layer coding of video signals for VBR networks

Two-layer conditional-replenishment coding of video signals over a variable-bit-rate (VBR) network is described. A slotted-ring network based on an Orwell protocol is assumed, where transmission of certain packets is guaranteed. The two-layer coder produces two output bit streams: the first bit stream contains all the important structural information in the image and is accommodated in the guaranteed capacity of the network, while the second adds the necessary quality finish. The performance of the coder is tested with CIF standard sequences and broadcast-quality pictures. The portion of the VBR channel allocated to the lower layer as guaranteed bandwidth is examined. Using broadcast-quality pictures, statistics were obtained on the performance of this system for different choices of bit rate in the lower layer. The effect of lost packets is shown on CIF standard picture sequences. It is shown that the coder performs well for a guaranteed channel rate as low as 10-20% of the total bit rate     

Optimization of image coding algorithms and architectures usinggenetic algorithms

This paper addresses the application of genetic algorithm (GA)-based optimization techniques to problems in image and video coding, demonstrating the success of GAs when used to solve real design problems with both performance and implementation constraints. Issues considered include problem representation, problem complexity, and fitness evaluation methods. For offline problems, such as the design of two-dimensional filters and filter banks, GAs are shown to be capable of producing results superior to conventional approaches. In the case of problems with real-time constraints, such as motion estimation, fractal search and vector quantization codebook design, GAs can provide solutions superior to those reported using conventional techniques with comparable implementation complexity. The use of GAs to jointly optimize algorithm performance in the context of a selected implementation strategy is emphasized throughout and several design examples are included     

Obstacle detection radar for cars

Work on radar systems for cars has been going on since the 1950s, but that earlier work did not lead to practical products. The paper reviews some of that earlier work, and shows how recent technological advances have now made automotive radar practical. It also shows some results obtained from current work in this field     

MLD and mse algorithms for adaptive detection of digital signals in the presence of interchannel interference

Adaptive mean-square error (mse) and maximum-likelihood detection (MLD) algorithms for a dual-channel digital communication system in the presence of interchannel interference and white Gaussian noise are presented. The mse algorithm forms estimates of the transmitted symbols from a linear combination of received symbols using weights that minimize the mse between transmitted and estimated symbols. The nonlinear MLD algorithm minimizes the probability of symbol error by maximizing the probability of the received signal samples on the two channels over ail possible transmitted symbol pairs. The probability of error is derived for the two algorithms when quadrature phase-shift keying (QPSK) is used as a modulation technique, and is compared with that of a dual-channel QPSK system having no compensation for the crosstalk.     

On the detection of known binary signals in Gaussian noise of exponential covariance

The optimum test statistic for the detection of binary sure signals in stationary Gaussian noise takes a particularly simple form, that of a correlation integral, when the solution, denoted byq(t), of a given integral equation is well behaved(L_{2}). For the case of a rational noise spectrum, a solution of the integral equation can always be obtained if delta functions are admitted. However, it cannot be argued that the test statistic obtained by formally correlating the receiver input with aq(t)which is notL_{2}is optimum. In this paper, a rigorous derivation of the optimum test statistic for the case of exponentially correlated Gaussian noiseR(tau) = sigma^{2} e^{-alpha|tau|}is obtained. It is proved that for the correlation integral solution to yield the optimum test statistic whenq(t)is notL_{2}, it is sufficient that the binary signals have continuous third derivatives. Consideration is then given to the case where a, the bandwidth parameter of the exponentially correlated noise, is described statistically. The test statistic which is optimum in the Neyman-Pearson sense is formulated. Except for the fact that the receiver employsalpha_{infty}(which in general depends on the observed sample function) in place ofalpha, the operations of the optimum detector are unchanged by the uncertainty inalpha. It is then shown that almost all sample functions can be used to yield a perfect estimate ofalpha. Using this estimate ofalpha, a test statistic equivalent to the Neyman-Pearson statistic is obtained.     

Encoding of analog signals for binary symmetric channels

Various encoding schemes are examined from the point of view of minimizing the mean magnitude error of a signal caused by transmission through a binary symmetric channel. A necessary property is developed for optimal codes for any binary symmetric channel and any set of quantization levels. The class of optimal codes is found for the case where the probability of error is small but realistic. This class of codes includes the natural numbering and some unit distance codes, among which are the Gray codes.     

雷达辐射源信号识别结果评估方法研究

针对雷达辐射源信号识别结果评价方法杂乱,指标单一等问题,提出一种新的信号识别结果评估体系结构,将识别率测试结果引入到雷达辐射源信号识别结果评估中,构建了基于识别率测试结果的雷达辐射源信号识别结果评估指标体系,建立了评估指标的层次结构模型,应用模糊综合评价法对识别结果进行评估,并对三种识别方法进行了计算机仿真评估实验,验证了新方法的可行性.     

Bit error rate of binary and quaternary DPSK signals with multipledifferential feedback detection

A differentially coherent detection scheme with improved bit error rate (BER) performance is presented for differentially encoded binary and quaternary phase shift keying (PSK) modulation. The improvement is based on using L symbol detectors with delays of 1, 2, . . ., L symbol periods and on feeding back detected PSK symbols. Exact formulas for the bit error probability are derived for the case that correct symbols are fed back. The effect of symbol errors in the feedback path on the BER is determined by computer simulations     

Joint source-channel turbo coding for binary Markov sources

We investigate the construction of joint source-channel (JSC) turbo codes for the reliable communication of binary Markov sources over additive white Gaussian noise and Rayleigh fading channels. To exploit the source Markovian redundancy, the first constituent turbo decoder is designed according to a modified version of Berrou's original decoding algorithm that employs the Gaussian assumption for the extrinsic information. Due to interleaving, the second constituent decoder is unable to adopt the same decoding method; so its extrinsic information is appropriately adjusted via a weighted correction term. The turbo encoder is also optimized according to the Markovian source statistics and by allowing different or asymmetric constituent encoders. Simulation results demonstrate substantial gains over the original (unoptimized) Turbo codes, hence significantly reducing the performance gap to the Shannon limit. Finally, we show that our JSC coding system considerably outperforms tandem coding schemes for bit error rates smaller than 10/sup -4/, while enjoying a lower system complexity.     

Real-time Doppler analysis of radar signals

Pulse Doppler radar Fourier analysis usually requires bulky and complex circuits to obtain a real-time implementation. The letter suggests the feasibility of a spectral analyser by means of commercial programmable gate array devices (PGAs) using Curtis and Wickenden's prime radix recursive algorithm transform' (PRAT). PRAT leads to simple and regular networks, which can be easily fitted in the proposed devices and then transferred to gate arrays.<>