一种基于多点测距信息的复合制导方法

分析探讨了一种用于提高弹道式导弹对目标命中精度的复合制导方案，提出了通过进行多点测距，利用状态转移矩阵方法，来估计导弹落点偏差和末修级起控点飞行状态参数，然后再按照需要的速度进行末修级导引控制的复合制导方案，并通过仿真计算分析论证了该方法的可行性。     

Fiber optic fence sensor developments

Many detection technologies have been employed for perimeter detection, to sensitize a barrier. These outdoor perimeter fence detection sensors must reliably detect intruders attempting to cut or climb the barrier, while ignoring the effects of environmental noise, including nearby activity. In recent conference proceedings, the new IntelliFIBER/spl trade/ fiber optic based product was introduced and compared with previous technologies. IntelliFIBER is designed to provide the advantages of a nonconductive "dielectric" cable sensor, e.g., resistance to electromagnetic interference and the ability to provide longer cable zones. It utilizes the proven processor of the Intelli-FLEX/spl trade/ triboelectric cable fence sensor, which provides relay or bidirectional networked serial communications and is compatible with its calibration module. IntelliFIBER also capitalizes on the Intelli-FLEX's adaptive detection algorithms that were developed through extensive field-testing, to provide exceptional immunity to environmental alarms while still detecting the skilled intruder.     

电工电子线路虚拟实验室的建设与应用

虚拟技术的发展使电子线路的分析设计过程得以在计算机上轻松、准确、快捷地完成。这样,一方面克服了实验室在元器件和规格上的限制,避免了损坏仪器等不利因素,另一方面使得实验不受时间及空间的限制,从而促进电子线路实验教学的现代化。     

Synthetic-aperture radar processing using fast factorized back-projection

Exact synthetic aperture radar (SAR) inversion for a linear aperture may be obtained using fast transform techniques. Alternatively, back-projection integration in time domain can also be used. This technique has the benefit of handling a general aperture geometry. In the past, however, back-projection has seldom been used due to heavy computational burden. We show that the back-projection integral can be recursively partitioned and an effective algorithm constructed based on aperture factorization. By representing images in local polar coordinates it is shown that the number of operations is drastically reduced and can be made to approach that of fast transform algorithms. The algorithm is applied to data from the airborne ultra-wideband CARABAS SAR and shown to give a reduction in processing time of two to three orders of magnitude.     

Almost instant time inference for hybrid partially dynamic Bayesian networks

A Bayesian network (BN) is a compact representation for probabilistic models and inference. They have been used successfully for many military and civilian applications. It is well known that, in general, the inference algorithms to compute the exact a posterior probability of a target node given observed evidence are either computationally infeasible for dense networks or impossible for general hybrid networks. In those cases, one either computes the approximate results using stochastic simulation methods or approximates the model using discretization or a Gaussian mixture model before applying an exact inference algorithm. This paper combines the concept of simulation and model approximation to propose an efficient algorithm for those cases. The main contribution here is a unified treatment of arbitrary (nonlinear non-Gaussian) hybrid (discrete and continuous) BN inference having both computation and accuracy scalability. The key idea is to precompile the high-dimensional hybrid distribution using a hypercube representation and apply it for both static and dynamic BN inference. Since the inference process essentially becomes a combination of table look-up and some simple operations, the method is shown to be extremely efficient. It can also he scaled to achieve any desirable accuracy given sufficient preprocessing time and memory for the cases where exact inference is not possible     

Recent Breakthroughs in RF Photonics for Radar Systems

Radar systems require transmission of very high purity signals. Photonics is now mature enough to achieve analog transmission with very low noise, strong immunity, and wide-bandwidth even in harsh environments. We present our recent developments of optimized optical links dedicated to radar and multifunction systems     

Two Methods of Spectral Estimation for SARSAT Signals

Search and rescue satellite aided tracking (SARSAT) depends on the processing of emergency locator transmitter (ELT) signals which are received by a satellite in low polar orbit. Since the signal from a distressed vehicle is normally immersed in a background of other ELT signals (false alarms), interference, and noise, different methods of spectral estimation can provide advantages in estimating carrier frequency. A comparison between average spectrum and minimum spectrum for several real signals is provided here.     

Spiral evolution applied to legacy avionics systems

The US Department of Defense (DoD), through the Office of the Secretary of Defense (OSD), has determined that evolutionary acquisition is their strategy of choice for future software-intensive systems, and that the spiral development model (SDM) is the preferred method/process for software-intensive development life cycles. Electronic Systems Command (ESC) at Hanscom AFB, Massachusetts, has written a draft handbook on the use of Spiral Development for all future Command and Control (C2) systems, including reference to the DoD 5000 series and Air Force Program Directive 63-1, Acquisition System, which deploys this OSD mandate for future C2 systems. Barry Boehm's continued work on SDM which he conceived in the 1980s, is heavily biased toward development of new systems that are software-intensive, as noted in a workshop he gave at the Software Engineering Institute (SEI) in 2000.     

Automotive-grade MEMS sensors used for general aviation

The attitude heading reference system (AHRS) provides data for primary flight instruments, head-up displays, autopilots, and moving map navigation systems. Advances in solid-state MEMS rate sensors, coupled with Kalman filter algorithms designed to mitigate high drift rates, provide the basis for low-cost, high-performance AHRS for general aviation. This paper describes the performance of a low cost, miniaturized AHRS using automotive-grade MEMS sensors. The performance of the system is detailed. The implications for certification of this class of system and fault tolerance are discussed.     

Performance evaluation for MAP state estimate fusion

This paper presents a quantitative performance evaluation method for the maximum a posteriori (MAP) state estimate fusion algorithm. Under ideal conditions where data association is assumed to be perfect, it has been shown that the MAP or best linear unbiased estimate (BLUE) fusion formula provides the best linear minimum mean squared estimate (LMMSE) given local estimates under the linear Gaussian assumption for a static system. However, for a dynamic system where fusion is recursively performed by the fusion center on local estimates generated from local measurements, it is not obvious how the MAP algorithm will perform. In the past, several performance evaluation methods have been proposed for various fusion algorithms, including simple convex combination, cross-covariance combination, information matrix, and MAP fusion. However, not much has been done to quantify the steady state behavior of these fusion methods for a dynamic system. The goal of this work is to present analytical fusion performance results for MAP state estimate fusion without extensive Monte Carlo simulations, using an approach developed for steady state performance evaluation for track fusion. Two different communication strategies are considered: fusion with and without feedback to the sensors. Analytic curves for the steady state performance of the fusion algorithm for various communication patterns are presented under different operating conditions.