Hough transform for long chirp detection

The online detection of a very long and weak chirp signal is studied. The signal has an extremely slowly decreasing frequency, and is corrupted by white Gaussian noise and possibly also by powerful tones. By exploring and comparing candidate methods, it is found that the Hough transform (HT) detector appears to be most suitable given constraints on computational load and detectability. The analytical and the simulational performance of the HT detector are obtained and compared with the analytical performance of the generalized likelihood ratio test (GLRT), which is assumed to be optimal. Applying a suitable threshold for the HT can increase speed dramatically while preserving performance. We have found that both dithering (taking varied frequency shifts for fast Fourier transforms (FFTs)) and increasing the FFT length can reduce the minimum detectable frequency slope with nearly no additional computation     

Passive tracking scheme for a single stationary observer

While there are many techniques for bearings-only tracking (BOT) in the ocean environment, they do not apply directly to the land situation. Generally, for tactical reasons, the land observer platform is stationary; but, it has two sensors, visible and infrared, for measuring bearings and a laser range finder (LRF) for measuring range. There is a requirement to develop a new BOT data fusion scheme that fuses the two sets of bearing readings, and together with a single LRF measurement, produces a unique track. This paper first develops a parameterized solution for the target speeds, and then heading, prior to the occurrence of the LRF measurement, when the track is unobservable. At, and after the LRF measurement, a BOT, formulated as a least squares (LS) estimator, then produces a unique LS estimate of the target states. Bearing readings from the other sensor serve as instrumental variables in a data fusion setting to eliminate the bias in the BOT estimator. The result is an unbiased and decentralized data fusion scheme. Results from two simulation experiments have corroborated the theoretical development and show also that the scheme is optimal.     

Electrolytes in femur and plasma of rats during prolonged restriction of motor activity.

Hypokinesia (decreased motor activity) induces insignificant bone mineral changes. The aim of this study was to measure mineralization, density, and also electrolyte content in the femur of rats during prolonged hypokinesia (HK). Studies were done on 144 male Wistar rats (370-390 g) during 15 days period of pre-HK and 90 days period of HK. Rats were equally divided into two groups: hypokinetic rats (HKR) and vivarium control (VCR). The HKR group of rats was kept in small individual cages. Femur mineralization density, ash mineral content, calcium (Ca) and phosphate (P) content, and plasma Ca and P concentration were measured. In the HKR group body weight, femur mineralization, density, ash mineral content, Ca and P concentration decreased significantly (p < or = 0.01) while plasma Ca and P concentration increased significantly (p < or = 0.01) when compared with the VCR group. The measured parameters did not change significantly in the VCR group when compared with the baseline control values. It was concluded that prolonged HK induces a significant reduction in electrolyte concentration accompanied by decreased mineralization, density, and ash mineral content of the femur of rats.     

Tracking considerations in selection of radar waveform for rangeand range-rate measurements

The conventional approach for tracking system design is to treat the detection and tracking subsystems as completely independent units. However, the two subsystems can be designed jointly to improve system (tracking) performance. It is known that different radar signal waveforms result in very different resolution cell shapes (for example, a rectangle versus an eccentric parallelogram) in the range/range-rate space, and that there are corresponding differences in overall tracking performance. We develop a framework for the analysis of this performance. An imperfect detection process, false alarms, target dynamics, and the matched filter sampling grid are all accounted for, using the Markov chain approach of Li and Bar-Shalom. The role of the grid is stressed, and it is seen that the measurement-extraction process from contiguous radar "hits" is very important. A number of conclusions are given, perhaps the most interesting of which is the corroboration in the new measurement space of Fitzgerald's result for delay-only (i.e., range) measurements, that a linear FM upsweep offers very good tracking performance     

The Sunyaev–Zeldovich Effect: Recent Work

Scattering of the cosmic microwave background (CMB) radiation by hot gas in clusters of galaxies produces a unique spectral signature – the Sunyaev–Zeldovich (S–Z) effect – that constitutes an important cosmological probe. The effect has been sensitively measured in more than 40 clusters, mostly with ground-based interferometric arrays operating at low microwave frequencies. These measurements have already yielded important information on cluster masses, and the Hubble constant. The scientific yield will be greatly increased when spectral and high-resolution spatial measurements of the effect in a large sample of nearby clusters will be made with stratospheric telescopes equipped with bolometric arrays. I review the current status of observational and theoretical S–Z work, and describe the main goals and challenges of using the effect as a more precise probe of cluster properties and cosmological parameters.     

车辆性能与尾气监测集成系统的研制

探讨了一种车辆性能与尾气监测系统(VPEMS)的设计.该系统装有发动机管理系统(EMS),具有多种传感器系统车辆的接口能力.文中阐述了适用于验证柴油机和汽油机数据的程序方法.VPEMS原型系统的试验包括对两台装有各种仪器车辆的试验台测试及野外测试.试验结果表明,每个子系统均达到了预定指标,其中一氧化碳、二氧化碳和一氧化氮量与实际监测值的偏差分别小于11.5%, 8.1%和17.7%.基于试验结果,文中给出了一个创建车辆性能、尾气与时间和空间相关的参考数据库实例.     

On joint track initiation and parameter estimation under measurement origin uncertainty

The problem of joint detection and estimation for track initiation under measurement origin uncertainty is studied. The two well-known approaches, namely the maximum likelihood estimator with probabilistic data association (ML-PDA) and the multiple hypotheses tracking (MHT) via multiframe assignment, are characterized as special cases of the generalized likelihood ratio test (GLRT) and their performance limits indicated. A new detection scheme based on the optimal gating is proposed and the associated parameter estimation scheme modified within the ML-PDA framework. A simplified example shows the effectiveness of the new algorithm in detection performance under heavy clutter. Extension of the results to state estimation with measurement origin uncertainty is also discussed with emphasis on joint detection and recursive state estimation.     

Explicit Expressions for the Bias and Variance of the ML Estimated Gumbel Distribution Parameters

Explicit expressions are derived for the bias and the variance of the maximum likelihood (ML) estimator of the Gumbel distribution.     

Estimation near "Zero Information" points: angle-of-arrival near the endfire

We examine large-sample properties of the maximum- likelihood estimator (MLE) in the vicinity of points where the Fisher information measure (FIM) equals zero. Under mild regularity conditions the MLE is asymptotically efficient and therefore lower bounded by the Cramer-Rao lower bound (CRLB) [5], which diverges for such points. When a linear sensor array is used for angle-of-arrival (AOA) estimation, the CRLB diverges as the AOA approaches pi/2. We provide new results characterizing the MLE performance in the AOA problem.     

Multiassignment for tracking a large number of overlapping objects[and application to fibroblast cells]

In this paper we present a new technique for data association using multiassignment for tracking a large number of closely spaced (and overlapping) objects. The algorithm is illustrated on a biomedical problem, namely the tracking of a group of fibroblast (tissue) cells from an image sequence, which motivated this work. Because of their proximity to one another and due to the difficulties in segmenting the images accurately from a poor-quality image sequence, the cells are effectively closely spaced objects (CSOs). The algorithm presents a novel dichotomous, iterated approach to multiassignment using successive one-to-one assignments of decreasing size with modified costs. The cost functions, which are adjusted depending on the “depth” of the current assignment level and on the tracking results, are derived. The resulting assignments are used to form, maintain and terminate tracks with a modified version of the probabilistic data association (PDA) filter, which can handle the contention for a single measurement among multiple tracks in addition to the association of multiple measurements to a single track. Estimation results are given and compared with those of the standard 2D one-to-one assignment algorithm. It is shown that iterated multiassignment results in superior measurement-to-track association. The algorithms presented can be used for other general tracking problems, including dense air traffic surveillance and control