Decentralized detection over multiple-access channels

We study the decentralized detection problem in a general framework where arbitrary number of quantization levels at the local sensors are allowed, and transmission from the sensors to the fusion center is subject to both noise and interchannel interference. We treat both Bayesian and Neyman-Pearson approaches to the problem, and develop an iterative descent algorithm to design the optimal quantizers and fusion rule. Some numerical examples for both approaches are also presented     

Comparison of signal estimation using calibrated and uncalibrated arrays

We consider the problem of separating and estimating the waveform of superimposed signals received by an array of sensors. If the array is well calibrated it is possible to first estimate the directions of arrival (DOA) of the signals and then use this information to separate the signals. When the array is not calibrated, but the array elements have the same unknown gain pattern, up to an unknown multiplicative factor and the phases of the elements are arbitrary and unknown, it is possible to estimate the array steering vectors and then use this information for signal estimation. We compare the quality of the estimated signals in the calibrated case with the quality of the estimated signals in the uncalibrated case, in terms of the output signal-to-interference ratio (SIRO) and output signal-to-noise ratio (SNRO).     

Explicit solutions for some simple decentralized detection problems

A decentralized detection problem is considered in which a number of identical sensors transmit a finite-valued function of their observations to a fusion center which makes a final decision on one of M alternative hypotheses. The authors consider the case in which the number of sensors is large, and they derive (asymptotically) optimal rules for determining the messages of the sensors when the observations are generated from a simple and symmetrical set of discrete distributions. They also consider the tradeoff between the number of sensors and the communication rate of each sensor when there is a constraint on the total communication rate from the sensors to the fusion center. The results suggest that it is preferable to have several independent sensors transmitting low-rate (coarse) information instead of a few sensors transmitting high-rate (very detailed) information. They also suggest that an M-ary hypothesis testing problem can be viewed as a collection of M(M-1)/2 binary hypothesis testing problems. From this point of view the most useful messages (decision rules) are those that provide information to the fusion center that is relevant to the largest possible numbers of these binary hypothesis testing problems     

Multisignal time delay detection and tracking

An optimum solution to the time delay detection and tracking problem for a single signal is extended to the multisignal problem where the number of signals present in the observed data (if any) is unknown. The number of signals present is determined, and the time delay of each detected signal is tracked. The number of possible global, or first level, hypotheses is large because of the exponential dependence on the number of potential signals. An efficient approximate multisignal detection and tracking solution that is as near optimum as possible for the computational resources required is developed. It has the form of parallel detector-trackers (one for each potential signal) each similar to the single-signal case, with communication between them. Test results demonstrate the utility of the approach     

Sensor Fault Detection in a System with Random Disturbances

Sensor faults are detected in an operating automatic system by a simplified version of the dedicated observer scheme. Control inputs are augmented by a random disturbance of moderate intensity. The dedicated observer in this case is a Kalman filter, driven by a single sensor. This filter provides estimates of the outputs from the other, nonredundant, sensors. A logical combination of these functionally redundant signals with the actual sensor signals provides prompt detection of incipient faults on all instruments without false alarms. The scheme is applied to a simulation of the lateral axis control system of a hydrofoil boat in which four sensors are to be covered by the fault detection scheme. Tests indicate that the scheme is robust with respect to variations in the intensity of the random disturbance.     

Distributed binary integration

A distributed radar detection system that employs binary integration at each local detector is studied. Local decisions are transmitted to the fusion center where they are combined to yield a global decision. The optimum values of the two thresholds at each local processor are determined so as to maximize the detection probability under a given probability of false alarm constraint. Using an important channel model, performance comparisons are made to determine the integration loss     

Local SNR considerations in decentralized CFAR detection

We consider the decentralized detection problem, involving N sensors and a central processor, in which the sensors transmit unquantized data to the fusion center. Assuming a homogeneous background for constant false-alarm rate (CFAR) analysis, we obtain the performances of the system for the Swerling I and Swerling III target models. We demonstrate that a simple nonparametric fusion rule at the central processor is sufficient for nearly optimum performance. The effect of the local signal-to-noise ratios (SNRs) on the performances of the optimum detector and two suboptimum detectors is also examined. Finally, we obtain a set of conditions, related to the SNRs, under which better performance may be obtained by using decentralized detection as compared with centralized detection     

基于有限元模型的飞行器柔性附件分散化滑模控制

研究分散化滑模控制在大型柔性附件振动控制领域中的应用。在设计控制系统时,滑模控制滑模面通过最小化最优价值函数得到,控制器采用饱和控制器。受控系统受到任意不可测量和不确定性外部扰动以及初始位移。分别利用分散化控制和集中控制方法对结构进行控制,仿真结果表明,当具有初始位移或受到不确定性外扰时,分散化控制非常有效。最后研究表明分散化控制方法所求解的Riccati方程数量远远少于集中控制方法,特别是大系统。     

A unified approach to the design of decentralized detection systems

A unified approach to the design of decentralized detection networks with arbitrary topologies is proposed and analyzed. In this approach, a decentralized detection system of arbitrary topology is represented by a communication matrix that specifies the interconnection structure of the detection network. This matrix is used to derive the general decision rule using the person-by-person-optimal (PBPO) solution methodology. It is shown that the PBPO decision rule is a likelihood ratio test for statistically independent observations. The threshold of the test is shown to be a function of the decision input vector of the detector under consideration. This unified approach is used to obtain the PBPO decision rules of decentralized detection systems with various topologies. Various results in the literature are verified. In addition, the PBPO decision rules for a decentralized detection system with peer communication are presented. Numerical examples are presented for illustration     

Optimal Data Fusion in Multiple Sensor Detection Systems

There is an increasing interest in employing multiple sensors for surveillance and communications. Some of the motivating factors are reliability, survivability, increase in the number of targets under consideration, and increase in required coverage. Tenney and Sandell have recently treated the Bayesian detection problem with distributed sensors. They did not consider the design of data fusion algorithms. We present an optimum data fusion structure given the detectors. Individual decisions are weighted according to the reliability of the detector and then a threshold comparison is performed to obtain the global decision.     

A Method for Selection of an Optimum Communication Link

A method is presented for the selection of a communication system based upon optimization of both frequency-dependent and frequency independent parameters. The indicator of quality used is the effective radiated power per cycle per second of information bandwidth. The method involves consideration of the frequency-dependent qualities such as system temperature and propagation losses independently from the frequency-independent quantities such as modulation loss, signal-to-noise ratio, performance margin, etc. Except for temperature and propagation loss effects, the method is made frequency-independent by considering the spacecraft antenna in terms of area while the ground terminal antenna is treated in terms of gain, thus removing wavelength from the transmission equation. An example is presented of the application of the method to the selection of a system for transmission of wide-band video signals over a satellite to earth link. The example illustrates the exchanges that can be made between the frequency-dependent and -independent quantities in order to arrive at an optimum system.     

Radar Waveform Synthesis by Mean Square Optimization Techniques

The synthesis of the phase-modulated waveform whose ambiguity function is the optimum estimate of some desired ambiguity function is accomplished by expanding the phase modulation in an orthogonal series. The ambiguity function x (?, ?d)|2 and the value of an arbitrary cost function defined on the (?, ?d) plane are then expressed in terms of the coefficients of the orthogonal series. The optimum waveform can then be determined by solving the variational equations for the coefficients. Numerical examples are presented for the case where it is desired to synthesize a desired ambiguity function x(?, ?d) for some rectangular region of the (?, ?d) plane.     

去中心化时差频差直接定位方法

针对原始利用时差频差的直接定位(DPD)方法存在数据传输量和计算量大的瓶颈,提出了两种去中心化直接定位方法。第1种方法采用去中心化配对方案,只将各观测站截获信号在站间进行一次传输,将数据传输和计算分散到各观测站间并行计算互模糊函数(CAF),构造仅满足满秩条件的互模糊矩阵(CAM)。第2种方法根据推导的任意互模糊函数间关系公式,采用归约方式去中心化的在各观测站并行计算余下互模糊函数,补全互模糊矩阵。两种方法都降低了直接定位数据传输量,提高了计算效率。性能分析和仿真实验表明本文两种方法精度性能优于两步定位方法,在低信噪比时两种方法都可达到比较理想的精度性能,在高信噪比时第2种方法与原始直接定位方法的精度性能相当。     

高可靠小条件数压缩感知叶尖定时信号辨识

为增强基于任意角度压缩感知(CS)叶尖定时信号(BTT)重构的稳定性,采用小生境微种群遗传算法提出了基于小条件数的高稳定性传感器安装布置方法。研究发现:任意角度CS的恢复矩阵条件数越小,不同信噪比下同步和非同步振动信号重构误差越趋于稳定在较低范围,优化后发现条件数为1的排布方案下,相邻传感器角度间隔趋向于均布2m取K的形式。利用条件数为1的矩阵冗余特性,设计了高可靠性的传感器排布方案,数值试验和有限元仿真验证表明叶尖定时系统在失效一个传感器的情况下仍可稳定得到准确的重构结果。在信噪比为5 dB时,冗余排布相比参考排布的主倍频幅值重构误差降低4.4%以上,验证了采用最小条件数排布的任意角度CS信号辨识方法在噪声及传感器失效情况下仍可保证BTT测量结果的有效性和可靠性。      

变截面梁式压电智能板振动控制的小波模式

基于 Daubechies小波理论的尺度函数变换 ,对于变截面悬臂板结构的弯曲建立了由压电片感应器的观测电量识别挠曲变形构形的显式关系式。此基础上 ,采用具有位移与速度信号负反馈控制律后 ,建立了抑制振动的压电动力控制程序。由于小波尺度函数逼近具有低带通性质 ,即具有自动滤除高频分量的能力 ,该控制程序将不会出现由观测溢出与控制溢出耦合而造成的控制失稳 (即在抑制低频 (阶 )扰动时系统激发出高频 (阶 )扰动的现象 )。数值仿真结果表明 :该控制方法所能控制的模态阶数与压电片数相同 ,而且其控制程序在抑制外界干扰方面是有效的。     

On optimal track-to-track fusion

Track-to-track fusion is an important part in multisensor fusion. Much research has been done in this area. Chong et al. (1979, 1986, 1990) among others, presented an optimal fusion formula under an arbitrary communication pattern. This formula is optimal when the underlying systems are deterministic, i.e., the process noise is zero, or when full-rate communication (two sensors exchange information each time they receive new measurements) is employed. However, in practice, the process noise is not negligible due to target maneuvering and sensors typically communicate infrequently to save communication bandwidth. In such situations, the measurements from two sensors are not conditionally (given the previous target state) independent due to the common process noise from the underlying system, and the fusion formula becomes an approximate one. This dependence phenomena was also observed by Bar-Shalom (1981) where a formula was derived to compute the cross-covariance of two track estimates obtained by different sensors. Based on this results a fusion formula was subsequently derived (1986) to combine the local estimates which took into account the dependency between the two estimates. Unfortunately, the Bayesian derivation made an assumption that is not met. This work points out the implicit approximation made and shows that the result turns out to be optimal only in the ML (maximum likelihood) sense. A performance evaluation technique is then proposed to study the performance of various track-to-track fusion techniques. The results provide performance bounds of different techniques under various operating conditions which can be used in designing a fusion system.     

一种基于最小流形长度的高精度线阵设计

 传统上以阵列孔径来比较各种线阵的测向性能,但这一指标没有考虑到阵元数目及阵列几何布局对阵列性能的影响。因子空间类算法需搜索阵列流形来进行测向,所以阵列流形对阵列性能有重要影响。阵列流形又是阵元数、阵列几何布局的函数,可通过阵列流形来研究阵元数、阵列几何布局与阵列测向性能的关系。在分析了线阵流形与线阵测向精度的关系的基础上,提出了一个基于线阵最小流形长度的指标来比较不同线阵的性能,该指标综合考虑了阵元数、阵列几何布局对阵列测向精度的影响。通过对此指标的讨论,给出了提高线阵测向精度的设计思路。对几个不同线阵的仿真证实了该指标的有效性,也验证了该设计思路的可行性。     

Calculating the performance of linear and square-law detectors

A method is presented for calculating the performance of linear and square-law detectors in detection schemes that employ noncoherent integration. The method consists of transforming the coherent characteristic function, which is usually easy to obtain to a noncoherent moment generating function describing the test statistic of a linear or square-law detector. The method provides a single mathematical framework for many signal models (both classical and new) and can be implemented using standard numerical routines. Although the method is not always optimum in terms of computing speed for specific classical models, its common approach for all signal models makes it very efficient in term of learning and implementation times. Classical results as well as results for an extended set of target models consisting of an arbitrary number of constant amplitude random phase returns are presented to demonstrate the technique. It is shown for the signal parameters considered that the performance difference between the linear and square-law detectors is relatively insignificant     

Bayesian Quickest Signal Detection in a Discrete-Time Observation

This paper deals with the problem of quickest detection of a signal in discrete-time observations where the noise is not necessarily additive. By introducing a new cost function, penalizing the decision delay, in addition to penalizing wrong decisions as in the classical case, a global risk function is derived for use in a Bayesian framework. The minimization of the average risk leads to the optimum Bayesian decision regions, giving the structure of the optimum receiver. Some simplifications for elementary costs and some applications are investigated. The optimum receiver is shown to be a parallel bank of classical optimum filters, each one matched to a particular delay of the signal to be detected. Our approach is shown to apply to the detection of certain changes in a stochastic process.