The Performance Characteristics of Two Extensions of the Sign Detector

Two related techniques have been proposed in the past for improving the performance of the sign detector through higherorder data quantization. The fixed-thresholdm-interval detector and the generalized sign detector using a conditional test are both nonparametric detectors which are fairly simple to implement. In this paper we compare the asymptotic and finite-sample, finite-signal performance characteristics of these two detectors, and point out their relative advantages and disadvantages.     

On the relationship between measures of discrimination and theperformance of suboptimal detectors

The problem of designing and analyzing suboptimal detectors via statistical distance measures is considered. As a preliminary result, we show that only the minimum and maximum probability of error are valid measures of discrimination between the input statistics. This result would seem then to imply that the use of distance measures in this context can be inappropriate. However, to overcome this apparent obstacle, we demonstrate explicit relationships between various f-divergences and the loss in performance of an arbitrary detector relative to the optimal detector. In particular, we establish both upper and lower bounds on the performance loss of a suboptimal detector in terms of the “distance” between the pertinent statistics of both the optimal and suboptimal detectors. While designing detectors by minimizing these upper bounds can be an elusive task, in many practical cases, the lower bound presented herein holds with equality. In this case, minimizing the separation of the output statistics of the detector with respect to a particular f-divergence equivalently minimizes the resulting probability of error of the detector. To facilitate design, other researchers have established conditions under which one may design arbitrary detection strategies with respect to a specific f-divergence (Kullback-Leibler distance being a principal example). We extend this approach by deriving necessary and sufficient conditions under which one may design detection strategies with respect to an arbitrarily chosen f-divergence. Thus when these conditions are met, one may optimize a detector with respect to the most analytically tractable distance measure to obtain the minimum probability of error detector over a selected class of detection strategies. Examples demonstrating the utility of this theory for the problem of designing optimal linear detectors and optimal signal sets are presented     

Efficient Implementation of Quasi- Maximum-Likelihood Detection Based on Semidefinite Relaxation

In this paper we develop two quasi-maximum likelihood (ML) channel detectors for multiuser detection: semidefinite relaxation (SDR) detector and phase-shift-keying (PSK) detector. These detectors can deliver near-ML bit error rate (BER) performance with a polynomial worst-case complexity. The SDR detector for binary-phase-shift-keying (BPSK) constellation is based on a convex SDR, whereas the PSK detector for $M$-PSK constellations is based on a nonconvex low-rank SDR. The SDR detector is implemented using a dual-scaling interior-point method, while the PSK detector is based on a coordinate descent strategy on a feasible region homotopy. We use dynamic dimension reduction and warm start techniques to achieve signal-to-noise ratio (SNR)-sensitive improvements for both detectors. Numerical simulations of BER performance and running time indicate the effectiveness of the two quasi-ML detectors when compared to the conventional sphere decoder and its variants.      

Design and analysis of robust detectors for TH IR-UWB systems with multiuser interference

In this letter, we design and analyze the performance of single-user-type non-linear detectors that are able to cope with the impulsive nature of multiuser interference (MUI) in timehopping impulse-radio ultra-wideband (TH IR-UWB) systems. We collectively refer to these detectors as "robust" detectors. We first propose two novel detectors and then derive semi-analytical expressions for the bit-error rate (BER) of TH IR-UWB with general robust detection. The evaluation of these expressions greatly facilitates the optimization of detector parameters and provides insight into the effects of MUI. A performance comparison shows that (1) robust detection significantly improves performance over conventional detection in the presence of MUI, (2) the parameters for various parametric robust detectors can be chosen to be constant over many transmission scenarios with only little performance degradation compared to using the optimal parameter value, and (3) the proposed two-term detector, which requires a modest amount of parameter estimation, achieves consistently the best performance.     

Multiuser detection for overloaded CDMA systems

Multiuser detection for overloaded code-division multiple-access (CDMA) systems, in which the number of users is larger than the dimension of the signal space, is of particular interest when bandwidth is at a premium. In this paper, certain fundamental questions are answered regarding the asymptotic forms and performance of suboptimum multiuser detectors for cases where the desired and/or interfering signal subspaces are of reduced rank and/or have a nontrivial intersection. In the process, two new suboptimum detectors are proposed that are especially well suited to overloaded systems, namely, the group pseudo-decorrelator and the group minimum mean-squared error (MMSE) detector. The former is seen to be the correct extension of the group decorrelator in the sense that it is the limiting form (in the low-noise regime) of the group MMSE detector. Pseudo-decorrelation is also used as a feedforward filter in a new decision feedback scheme. For the particular case of real-valued modulation, it is shown that the proposals of the so-called "improved" linear (also known as "linear-conjugate" or "widely linear") detectors were more simply derived earlier using the idea of minimal sufficiency, which we also apply to the new detectors of this paper.     

新型亚波长陷光结构HgCdTe红外探测器研究进展

综述了近几年来亚波长陷光结构Hg Cd Te红外探测器研究进展.系统介绍了一种结合有限元方法与时域有限差分方法对红外探测器的"光""电"特性进行联合模拟和设计方法,以及基于这种新的数值模拟方法对亚波长人工微结构Hg Cd Te红外探测器的模拟和分析结果.理论分析和实验研制数据均显示这种新型亚波长人工微结构结构具有很好的陷光特性,在提高长波红外探测器性能方面具有潜在应用前景.     

Impulse Noise Detector Performance Measure Based on Intensity Volume

An accurate detector performance evaluation method provides a fair comparison platform and can also support in parameter optimization for existing Impulse noise detectors in the applications of medical imaging. The Impulse noise detector performance measure (INDPM) package is widely applied as tools for quantitative comparison among detectors, which contains recall measure, accuracy measure, precision measure, specificity measure and F-measure. However, these five measures suffer from limited accuracy in correctly evaluating the performance of a detector and are not in well agreement with human subjective evaluation. To solve this problem, five new measures are proposed by introducing a new concept of intensity volume to form a new Impulse noise detector performance package (IV-INDPM). Using a standard image dataset, we conduct experimental and comparative tests with 32 different original images and 5 different existing detectors. Results demonstrate the superior performance of each new measure within IV-INDPM in reaching a much closer agreement with human subjective evaluation, compared to existing measures in INDPM. Even though five new measures are efficient in evaluating detectors’ performance from different perspectives, a new benchmark algorithm (IND-BA) is proposed as a robust and overall metric for ease of general-purpose use by making the most of these five new measures. Comparison results demonstrate its efficiency and accuracy.     

OSSO和OSGO恒虚警检测器在Pareto分布混响背景下的性能分析

Pareto分布是一种重要的非高斯分布,被证明能够有效描述高分辨率主动声纳的混响统计特性。文章分析了有序统计选小(Ordered Statistic with Smallest Option, OSSO)和有序统计选大(Ordered Statistic with Greatest Option, OSGO)两种恒虚警(Constant Fales Alarm Rate, CFAR)检测器在Pareto分布混响背景下的性能。在尺度参数已知情况下,证明了OSSO-CFAR和OSGO-CFAR对形状参数具有恒虚警的特性。进一步分析了两种检测器在均匀Pareto混响背景、多目标干扰及混响边缘情况下的性能,并与有序统计(Ordered Statistic, OS)CFAR进行了对比。结果表明,在均匀混响背景下,OSGO-CFAR的检测性能与OS-CFAR相近,在混响边缘情况下具有最好的虚警控制能力;而对于多目标干扰情况,OSSO-CFAR比其他两种检测器的检测性能更优。      

A differentially coherent PN code acquisition receiver for CDMAsystems

New differentially coherent detectors for acquisition of direct sequence spread-spectrum signals are introduced. These detectors are alternatives to the noncoherent detectors that have been considered almost exclusively in the past. The proposed detectors are suitable for commercial code-division multiple-access (CDMA) systems which operate with a relatively large noise floor and provide a surprisingly large signal-to-noise ratio (SNR) improvement over the noncoherent detectors of approximately 5 dB. Under the random code sequence assumption, an exact analysis of the differentially coherent detection performance for both full period correlation (FPC) and partial period correlation (PPC) is carried out. The detector performance in terms of detection and false alarm probabilities for both partial and full period correlations is investigated, and the results are compared with those of classical noncoherent detection. The mean acquisition time for both single-dwell and multiple-dwell acquisition schemes are compared with their noncoherent counterparts     

Detection Performance Considerations for Direct-Sequence and Time-Hopping LPI Waveforms

The implementation and performance of wide-band detectors for direct-sequence and time-hopping spread-spectrum waveforms in the presence of additive white Gaussian noise are considered in this paper. Of interest here is the performance penalty incurred when going from optimal to suboptimal detector structures. In both cases, performance is quantified by appropriately defined distance measures and is ultimately compared to that of the simplest hypothesis-discriminating device, namely, the energy detector (radiometer).     

Analysis and Performance Evaluation of Linear Multiuser Detectors in the Downlink of DS-CDMA Systems Applying Spectral Decomposition

This paper studies the performance of linear multiuser detectors for direct-sequence code division multiple access systems at different loading levels and users' powers, using singular value decomposition (SVD) techniques in the downlink of Rayleigh flat-fading and additive white Gaussian channels. The performance of the matched filter (MF), decorrelator (zero-forcing), and minimum mean-squared error (MMSE) detectors are studied and compared. Analytical and simulation results are also presented in terms of the bit error rate. From this analysis, a simple linear multiuser detector is developed that exploits the structure of the system's spreading codes matrix from the SVD viewpoint. Also, the numerical performance of this proposed detector is compared to that of the conventional detector (MF) as a function of the signal-to-noise ratio. Finally, the performance limits are established in terms of the singular values of the spreading codes matrix. Extensive simulation results validate the analysis presented in the paper for equal or unequal users' powers.     

Adaptive detection of statistical signals in noise

This paper deals with the forms and properties of a detector operating in an environment in which little statistical information about either the signal or noise field is or can be available. An adaptive detector based on the theory of nonparametric statistics has been designed for this purpose. The detector uses amplitude samples taken from two distinct receivers, only one of which may contain signals from a target. The detector maintains a constant false alarm rate despite any nonstationarity of the noise. The theory of nonparametric statistics suggests that the data from the two sources be ranked in order of amplitude, that a linear weighting (a correlator) be applied to the ranking, and the result be applied to a threshold. In this study, we have considered an adaptive detector of this form. The adaptation mechanism selects the weight (correlating) function on the basis of the past observed data. This class of adaptive detectors is shown to have excellent performance in terms of signal detectability for signals of adequate strength. However, for a given detector design, signals weaker than a certain critical threshold cannot be detected regardless of the amount of data available. Thus, in contrast to the kind of signal suppression effect which characterizes conventional passive detection schemes, the adaptive detector has a sharp minimum detectable signal threshold.     

Performance Analysis of Blind-Adaptive-Subspace Multiuser Detectors Over Multipath Fading Channels

Perturbation analyses for various kinds of blind-adaptive-subspace multiuser detectors are presented in this paper. Closed-form expressions are derived for the minimum-mean-square-error detector, zero-forcing detector, and group-blind detector in terms of output signal-to-interference-plus-noise ratio and bit-error rate over a multipath fading channel. Numerical results show that the analytical results match well with the simulation results for both static and dynamic environments. Furthermore, the proposed analytical results can be treated as performance bounds for other blind-adaptive singular-value-decomposition-based subspace multiuser detectors     

Robust transient signal detection using the oversampled Gaborrepresentation

The Gabor representation has been investigated previously as an effective and efficient means of detecting transient signals. The major problem associated with the most commonly used form of the Gabor representation is that it assumes that signals have integer arrival times and modulation frequencies-an assumption that, if violated, causes signal miss-match and deterioration in detector performance. The present correspondence presents the concept of oversampling the Gabor representation, which makes the representation more robust to certain types of signal mismatch. To show this, the performance of an oversampled Gabor detector is compared to that of critically sampled Gabor detectors. Gabor coefficients are calculated in the oversampled representation via the least squares method, which has been shown to be superior to the more commonly used biorthogonal function method in terms of corresponding detector performance     

Performance evaluation of differential and discriminator detection of continuous phase modulation

Recently, bandwidth efficient constant-amplitude digital modulation schemes have also been shown to be power efficient when coherent detection is used. Partial-response continuous phase modulation (CPM) schemes are within this class. In some applications noncoherent detection is preferred. The performance of CPM systems is analyzed for differential and discriminator detection. An additive white Gaussian channel is assumed. The detectors make symbol-by-symbol decisions. The considered schemes are M-ary with an arbitrary modulation index and pulse shaping over several symbol intervals. The performance is analyzed by means of error probability expressions. The IF filter for the detectors is optimized within a special class of filters to give good performance. The differential detector is also analyzed on a Rayleigh fading channel. The fading is assumed to be slow. The IF filter is also optimized on this channel. Simulated error probabilities for discriminator detection with a Viterbi detector are also presented both for the Gaussian and the Rayleigh fading channel. The discriminator detector making symbol-by-symbol decisions is simulated on the Rayleigh fading channel. It is shown that partial-response CPM schemes with good performance can also be obtained with noncoherent detectors.     

Low-Complexity Symbol Detector for MIMO-OFDM-Based Wireless LANs

In this brief, a low-complexity hardware architecture for multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) symbol detectors with two transmit and two receive antennas is proposed. The detectors support two MIMO-OFDM schemes of space-frequency block coded OFDM and space-division multiplexing OFDM in order to achieve higher performance and throughput. However, symbol detection processes for these two schemes have high computational complexity, which is a burden to hardware implementation of MIMO-OFDM symbol detectors. In order to reduce complexity, the proposed symbol detector is designed with shared architecture, where similar functional blocks are merged and share the hardware resources, and results in the reduction of logic gates by 34% over a conventional architecture employing two individual detectors     

Convolutional reconstruction algorithm for fan beam concave and convex circular detectors

A modified convolution-backprojection reconstruction algorithm for a circular detector with an arbitrary radius of curvature has been derived for fan-beam geometries. The algorithm reduces to conventional fan-beam algorithms for flat detectors and for curved detectors having whose radii of curvature coincident with the X-ray tube focal spot. The algorithm substitutes a power series of convolution integrals in place of a single convolution integral. Computer simulations have verified the validity of the algorithm for a detector that curves away from the X-ray source. In this case, it has been demonstrated that good reconstructions are obtained when only a few of the terms of the power series are retained. The development of this algorithm represents a first step toward a cone-beam reconstruction algorithm that eventually will be used for an image-intensifier-based computerized-tomography volume imager being developed in the authors' laboratory.     

Detection Schemes for Weak Signals in First-Order Moving Average of Impulsive Noise

In this paper, the detection of weak signals in additive noise described by the first-order moving average (FOMA) of an impulsive process is considered. Specifically, decision regions of the maximum likelihood (ML) and suboptimum ML (S-ML) detectors are derived in the FOMA noise model, and specific examples of the ML and S-ML decision regions are obtained. The ML and S-ML detectors are employed in the antipodal signaling system and compared in terms of bit error rate in an impulsive noise environment. Numerical results show that the S-ML detector, despite its reduced complexity and simpler structure, exhibits practically the same performance as the optimum ML detector. It is also observed that the performance gap between detectors for FOMA and independent and identically distributed noise becomes larger as the degree of noise impulsiveness increases     

Heterojunction III—V alloy photodetectors for high-sensitivity 1.06-µm optical receivers

A new type of 1.06-µm solid-state detector is discussed, the inverted hetrojunction III-V alloy mesa photodiode, which offers quantum efficiencies near 1.00 percent, extremely low capacitance and transit time, and low dark currents. The characterstics of these detectors allow their use in sensitive 1.06-µm optical receivers which promise better signal-to-noise ratios in a number of applications than any other available 1.06-µm photodetector. In particular, an optimization procedure for selecting photodiode and preamplifier parameters to give the best signal-to-noise ratio under signal conditions is discussed and this technique is applied to a proposed system application. It is shown that in this laser-illuminated airborne night imaging system, a small area heterojunction III-V alloy photodiode detector in an optimized receiver should be able to give signal-to-noise ratios much higher than any other 1.06-µm detector approach, even though the other 1.06-µm detectors may have lower noise equivalent power (NEP) values than this receiver. This is an illustration of the fact that such "magic numbers" for detector comparision as NEP are applicable only to comparing similar types of detectors in certain specific types of applications (such as comparing IR photoconductors in a high background application), and are of very little value in determining the relative performance of different types of detectors for a given system application (such as comparing photomultipliers, avalanche photodiodes, and low-noise photodiodes for this application).     

One- and Two-Stage Tunable Receivers

In this paper, we propose and assess a CFAR detector that can adjust its “directivity” through a real scalar parameter. It relies on the usual assumption that a set of homogeneous training data is available and encompasses as special cases the well-known Kelly's GLRT and the recently introduced W-ABORT detector. More important, it can be tuned in order to control the level to which sidelobe signals are rejected. Such functionality is particularly important to contain the number of false alarms in presence of mismatched signals. We also consider a parametric detector which resorts to a diagonally loaded sample covariance matrix commonly adopted to take advantage of the presence of strong interferers. The performance assessment of such detector has shown that it can significantly outperform Kelly's GLRT in terms of prediction probabilities for matched signals and in terms of selectivity, but it is not strictly CFAR. We also propose to use the CFAR parametric detector as second stage of a two-stage tunable detector and show that such a two-stage detector can outperform already proposed tunable receivers in terms of selectivity. The analysis of the detectors is conducted assuming a homogeneous Gaussian environment; with reference to this scenario and to the CFAR detectors we derive analytical expressions for the probability of false alarm and the probability of detection for both matched and mismatched signals.