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.     

Airborne radar: its beginnings in World War II

Although not realized at the time, the defeat of the German Air Force in the summer of 1940 was one of the crucial battles of World War II. The narrow margin of victory can be ascribed to Britain's air-warning radar, Chain Home (CH), consisting of the 15-meter CH and the 1.5-meter CHL. The skillful use of this equipment by the Royal Air Force made daylight bombing unsustainable; the Luftwaffe then turned to night attacks, generally called "The Blitz." These were not effective in destroying military and industrial targets and depended on the hope of reducing the population's will to fight. Chain Home was of little use except to observe the attackers arrival, as it had almost no ability to follow the attackers as they proceeded inland. This eventuality was reckoned with before the outbreak of hostilities and had called for radars mounted in night fighters capable of guiding the pilot close enough to the target for him to open fire visually. The electronic techniques used at 1.5-meters were adapted to planes capable of carrying the radar and its operator. But there were three important design constraints: 1) the antennas had to be restricted to sizes that were practical for installation on aircraft, which for meter waves gave them low gain and large side lobes; 2) the set's maximum range was limited by the fighter's altitude as a result of the huge ground returns from the side lobes. British antiaircraft artillery, the stepchild of their arms, was too ineffective to drive the bombers to extreme altitudes; and 3) a minimum range had to be held until the flier could see his target, which strained the pulse techniques of the time.     

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.     

Microdosimetric measurements of heavy ion tracks.

The biological effectiveness of radiations depends on the spatial pattern of ionizations and excitations produced by the charged particle tracks involved. Ionizations produced by both the primary ion and by energetic delta rays may contribute to the production of biologically relevant damage and to the concentration of damage which may effect the probability of repair. Although average energy concentration (dose) can be calculated using homogeneous track models, the energy is actually concentrated in small volumes containing segments of the ion and delta ray tracks. These local concentrations are studied experimentally using low pressure proportional counters, and theoretically, using Monte Carlo methods. Small volumes near an ion track may be traversed by a delta ray. If they are, the energy deposited will be similar to that produced by a single electron track in a low-energy x-ray irradiation. The probability of a delta ray interaction occurring decreases with the square of the radial distance from the track. The average energy deposited is the product of this probability and the energy deposited in an interaction. Average energy deposited calculated from measured interaction probability is in good agreement with the results of homogeneous track models.     

Design for validation

An approach is outlined for the development of ultrareliable avionics for civil air transports using a design-for-validation philosophy that includes rigorous application of formal methods. The basic concept of the methodology is introduced, and the role of formal methods is explored. The impact of the design-for-validation philosophy on the system design process is then demonstrated by two simple examples. More details about the design-for-validation methodology are then given