KUPS: Knowledge-Based Ubiquitous and Persistent Sensor Networks for Threat Assessment

We propose a knowledge-based ubiquitous and persistent sensor network (KUPS) for threat assessment, in which "sensor" is a broad characterization. It refers to diverse data or information from ubiquitous and persistent sensor sources such as organic sensors and human intelligence sensors. Our KUPS for threat assessment consists of two major steps: situation awareness using fuzzy logic systems (FLSs) and threat parameter estimation using radar sensor networks (RSNs). Our FLSs combine the linguistic knowledge from different intelligent sensors, and our proposed maximum-likelihood (ML) estimation algorithm performs target radar cross section (RCS) parameter estimation. We also show that our ML estimator is unbiased and the variance of parameter estimation matches the Cramer-Rao lower bound (CRLB) if the radar pulses follow the Swerling II model. Simulations further validate our theoretical results.     

Optimal Decision Fusion in Multiple Sensor Systems

The problem of optimal data fusion in the sense of the Neyman-pearson (N-P) test in a centralized fusion center is considered. The fusion center receives data from various distributed sensors. Each sensor implements a N-P test individually and independently of the other sensors. Due to limitations in channel capacity, the sensors transmit their decision instead of raw data. In addition to their decisions, the sensors may transmit one or more bits of quality information. The optimal, in the N-P sense, decision scheme at the fusion center is derived and it is seen that an improvement in the performance of the system beyond that of the most reliable sensor is feasible, even without quality information, for a system of three or more sensors. If quality information bits are also available at the fusion center, the performance of the distributed decision scheme is comparable to that of the centralized N-P test. Several examples are provided and an algorithm for adjusting the threshold level at the fusion center is provided.     

雷达和红外成像双传感器信息融合目标识别研究

提出了一种利用目标的雷达和红外成像２种独立的传感器信息的互补性来构造特征向量的信息融合方法——联合向量空间法,并用对应的自适应信息融合系统进行目标识别。仿真证实比用单传感器的效果明显优越,从而说明了本文方法的有效性。     

Tracking with distributed sets of proximity sensors using geometric invariants

We propose a new approach to forming an estimate of a target track in a distributed sensor system using very limited sensor information. This approach uses a central fusion system that collects only the peak energy information from each sensor and assumes that the energy attenuates as a power law in range from the source. A geometrical invariance property of the proximity of the distributed sensors relative to a target track is used to generate potential target track paths. Numerical simulation examples are presented to illustrate the practicality of the technique.     

Performance of Search via Track-Before-Detect for Distributed Sensor Networks

We consider the search for moving targets over large areas using a network of fixed sensor nodes. The concept of track-before-detect is defined and used to both manage the information between sensors and reduce the likelihood of false searches. We develop expressions for the probability of search success and the probability of reporting false search in this system concept. Using these as performance measures, we examine how the track-before-detect search strategy impacts design choices in these networks, by showing which parameter changes in the sensor design have the greatest impact on improving the desired performance goals.     

Electrical power on a 30 kW space-based radar satellite

An electrical power system for a space-based radar satellite is described. When the radar is on, its transmitter needs an average DC power of 30 kW. The problem of distributing the power efficiently in pulses to many transmit/receive modules is addressed. System requirements include a high-voltage battery and transmission line, load-sharing between the solar array, and the battery during sunlit periods, and a 25-kW solar array. A scaled-down version of the power system for a proof-of-concept demonstration is described     

A Fault-Tolerant Multisensor Navigation System Design

The problem of soft-failure tolerant estimation in navigationsystems composed of multiple inertial measurement clusters and oneor more reference sensors is addressed. A new approach ispresented that achieves containment of failed sensor data, andisolates the historic good data provided by the unfailed sensors.Multiple (local) estimates are computed where the estimates areconditioned on different subsets of the sensors. A statistical overlaptest is used to determine the validity of the local estimates, and afailed sensor can be identified from analysis of the invalid localestimates. After the time of detection the most accurate estimatebased on all but the failed sensor is identified. The results areapplied to a dual-inertial/Doppler radar navigation system andsimulation results are presented.     

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     

Multi-Target/Multi-Sensor Tracking using Only Range and Doppler Measurements

A new approach is described for combining range and Doppler data from multiple radar platforms to perform multi-target detection and tracking. In particular, azimuthal measurements are assumed to be either coarse or unavailable, so that multiple sensors are required to triangulate target tracks using range and Doppler measurements only. Increasing the number of sensors can cause data association by conventional means to become impractical due to combinatorial complexity, i.e., an exponential increase in the number of mappings between signatures and target models. When the azimuthal resolution is coarse, this problem will be exacerbated by the resulting overlap between signatures from multiple targets and clutter. In the new approach, the data association is performed probabilistically, using a variation of expectation-maximization (EM). Combinatorial complexity is avoided by performing an efficient optimization in the space of all target tracks and mappings between tracks and data. The full, multi-sensor, version of the algorithm is tested on simulated data. The results demonstrate that accurate tracks can be estimated by exploiting spatial diversity in the sensor locations. Also, as a proof-of-concept, a simplified, single-sensor range-only version of the algorithm is tested on experimental radar data acquired with a stretch radar receiver. These results are promising, and demonstrate robustness in the presence of nonhomogeneous clutter.     

Experimental Evaluation of Passive Microwave Velocity/Altitude Sensing

Experiments were conducted to determine the feasibility of using a passive microwave sensor of velocity/altitude ratio (V/H) as the basis for an aircraft navigation system. This sensor, combined with a radar altimeter, yields the velocity information needed for navigation. Airborne measurements were made with a two-beam X-band radiometer in a C-47 test aircraft. Radiometer signals and auxiliary information were recorded on magnetic tape. Ground-based data processing provided a comparison of radiometer-derived V/H measurements with those derived from independent sensors. Good results (fluctuating errors comparable to experimental uncertainties) were obtained over green farmland, urban areas, rice paddies, and certain desert areas; marginal results were obtained over other deserts and winter farmland. It was concluded that a microwave V/H sensor is feasible as the basis for a navigation system at low altitude over favorable terrains.     

Sensor fusion for intelligent alarm analysis

The purpose of an intelligent alarm analysis system is to provide complete and manageable information to a central alarm station operator by applying alarm processing and fusion techniques to sensor information. This paper discusses the sensor fusion approach taken to perform intelligent alarm analysis for the Advanced Exterior Sensor (AES). The AES is an intrusion detection and assessment system designed for wide-area coverage, quick deployment, low false/nuisance alarm operation, and immediate visual assessment. It combines three sensor technologies (visible, infrared, and millimeter wave radar) collocated on a compact and portable remote sensor module. The remote sensor module rotates at a rate of 1 revolution per second to detect and track motion and provide assessment in a continuous 360° field-of-regard. Sensor fusion techniques are used to correlate and integrate the track data from these three sensors into a single track for operator observation. Additional inputs to the fusion process include environmental data, knowledge of sensor performance under certain weather conditions, sensor priority, and recent operator feedback. A confidence value is assigned to the track as a result of the fusion process. This helps to reduce nuisance alarms and to increase operator confidence in the system while reducing the workload of the operator     

Surveillance system based on data fusion from image and acousticarray sensors

The present publication shows a model of a monitoring system of high benefit, based on two complementary sensorial systems (image+acoustics), which allows the information received to fuse, and to prioritize the computational resources toward the zones with considerable risk. The application uses components such as: active acoustic radar based on a phase array of microphones, with techniques of beamforming, and multibeam detection schemes; efficient compression algorithms and video transmission in real time. The system is composed of an arbitrary number of sensors (monitoring probes), distributed by the monitoring space, a data network and a central server (monitoring manager). The sensors consist of a microprocessor, with its memory and three main modules: (1) acoustic radar; (2) video capture card; and (3) network card. The flexibility of the system allows new modules to be added such as: personal detector card; sound card; cards for telecontrol; etc. The sensor microprocessor preprocesses the information received by the modules, packs and transmits it to the central server through a data network. The system uses IP protocol, and SNMPv2 for management     

Bounds on Time-Delay Estimation for Monochromatic Signals

Time-delay estimation (TDE) of monochromatic signals,observed by spatially separated sensors, is widely used for sourcelocalization in radar/sonar applications. We use lower bounds tostudy the accuracy of TDE as a function of signal to noise ratio(SNR), frequency, and sensor separation. We show that the Cramer-Rao bound, which is frequently used as a standard ofreference, yields optimistic predictions in many cases.     

多传感器融合目标跟踪

分析了基于成象和雷达两种传感器对目标状态的测量模型及其融合模型。针对两种传感器之间测量信息的不同步问题,给出了一种基于最小二乘法的不同步信息之间的时间配准和融合方法,并设计了跟踪滤波器。     

Event-triggered cooperative target tracking in wireless sensor networks

Since the issues of low communication bandwidth supply and limited battery capacity are very crucial for wireless sensor networks, this paper focuses on the problem of event-triggered cooperative target tracking based on set-membership information filtering. We study some fundamental properties of the set-membership information filter with multiple sensor measure-ments. First, a sufficient condition is derived for the set-membership information filter, under which the boundedness of the outer ellipsoidal approximation set of the estimation means is guaranteed. Second, the equivalence property between the parallel and sequential versions of the set-membership information filter is presented. Finally, the results are applied to a 1D event-triggered target tracking scenario in which the negative information is exploited in the sense that the measurements that do not satisfy the triggering conditions are modelled as set-membership mea-surements. The tracking performance of the proposed method is validated with extensive Monte Carlo simulations.     

基于最小跳数的无线传感器网络跨层设计

传统的严格分层参考模型无法实现对无线传感器网络资源的有效管理和运用,跨层设计是提高网络整体性能的一种有效方法。针对无线传感器网络能量、计算资源、存储资源和带宽资源有限的特点,提出一种基于最小跳数的路由层和MAC层的跨层协议设计方案。MAC层和路由层通过共享sensor节点到sink节点的最小跳数信息,在MAC层建立时间梯度,解决多个节点共享无线信道的问题;并在路由层建立路由表,解决路由选择问题。仿真结果表明,该方案在降低网络能耗的同时,在降低传输延迟,提高数据投递率方面也取得了良好的性能。     

Local node selection for localization in a distributed sensor network

This paper discusses a new localized resource manager for a wireless sensor network of bearings-only sensors. Specifically, each node uses knowledge of the target under surveillance to determine whether it should actively collect measurements and how far to disseminate the data in order for the sensor network to maintain track of the target. At each node, the resource manager requires only knowledge of the relative location to the target for itself and the active nodes from the previous snapshot. The decentralized strategy represents a modification to the global node selection (GNS) method that exploits knowledge of the location of all nodes in the network. Simulations show that despite the lack of global network knowledge, the new localized management method is almost as effective as GNS in terms of balancing the tradeoff between energy usage and localization accuracy.     

LEACH协议的改进与仿真研究

无线传感器网络由能量受限的节点组成,高效节能的路由算法是路由设计的关键问题。在LEACH算法的基础上,提出了一种新的分簇式路由策略,从簇头个数的确定、簇头选举方法对LEACH算法进行了改进,数据传输方式允许采用多跳方式与基站节点通信,仿真结果表明该算法具有降低网络能耗、延长网络生命周期的优点。     

Evaluating sensor technology for UAS collision avoidance

The problem of "sense-and-avoid" for Unmanned Aircraft Systems (UAS) is genuinely multi-dimensional: there is a wide range of UAS sizes, speeds, and maneuverability, as well as missions for which these UAS will be used. There are also a variety of sensors that might be used for sense-and-avoid, which have widely varying capabilities to measure distance or angle to an obstacle, as well as closing rate, and time to collision. Most sensors are not able to provide all required information about the geometry of an encounter; therefore, using a combination of sensors offers one possible solution. We are investigating the concept that there may be a variety of possible sensor solutions for each distinct UAS capability or mission. By studying the breadth of UAS types and missions, and selectively testing certain sensors in the field, we are evaluating the limits to the capabilities of sensors and sensor combinations. This report is on the progress of this multi-dimensional evaluation. We have scoped the dimensions for evaluating UAS capabilities and the capabilities of sensors. We are experimentally evaluating sensor parameters on a variety of aircraft to validate the specified capabilities. This reports on our methodology for field evaluation of sensor technology and the lessons learned on evaluation platforms and capabilities.     

Comparison of Two Major Classes of Coherent Pulsed Radar Systems

Two classes of coherent radar types are analyzed to ascertain whether any significant advantages exist for a given system. The classes compared are those coherent radars which transmit a phasecoherent pulse-to-pulse RF carrier as opposed to those which transmit randomly phased RF carriers but store the coherent information at the radar for Doppler extraction. Rigorous new analytical development is avoided in favor of examination of the considerable existing literature, examination of practical limitations, and synthesis of generic solutions from key concepts. Examination is made of coherent radar classes from the viewpoints of reconnaissance ance and intelligence measurement, new radar design and devlopment, and electronic countermeasures vulnerability. The conclusion that the classes of coherent radars examined have a priori and a posteriori equivalent performance has significant implications not published in any reference source.