Pulse-Position Modulation Based on Energy Detection

A pulse-position modulation (PPM) system based on energy detection is described. The system is shown to be applicable to a communication system in which the arrival times of signals are unknown. The decision statistics are chisquare distributed (either central or noncentral), and recursive methods of computing probabilities of error are derived. A simple digital processor for implementing the system is also described.     

Fast converging adaptive processor or a structured covariance matrix

The use of adaptive linear techniques to solve signal processing problems is needed particularly when the interference environment external to the signal processor (such as for a radar or communication system) is not known a priori. Due to this lack of knowledge of an external environment, adaptive techniques require a certain amount of data to cancel the external interference. The number of statistically independent samples per input sensor required so that the performance of the adaptive processor is close (nominally within 3 dB) to the optimum is called the convergence measure of effectiveness (MOE) of the processor. The minimization of the convergence MOE is important since in many environments the external interference changes rapidly with time. Although there are heuristic techniques in the literature that provide fast convergence for particular problems, there is currently not a general solution for arbitrary interference that is derived via classical theory. A maximum likelihood (ML) solution (under the assumption that the input interference is Gaussian) is derived here for a structured covariance matrix that has the form of the identity matrix plus an unknown positive semi-definite Hermitian (PSDH) matrix. This covariance matrix form is often valid in realistic interference scenarios for radar and communication systems. Using this ML estimate, simulation results are given that show that the convergence is much faster than the often-used sample matrix inversion method. In addition, the ML solution for a structured covariance matrix that has the aforementioned form where the scale factor on the identity matrix is arbitrarily lower-bounded, is derived. Finally, an efficient implementation is presented.     

On the false alarm probability for an overlapped FFT processor

A standard processor for detecting narrowband signals in noise applies the fast Fourier transform (FFT) to overlapped data blocks, and then sums the squared magnitudes of the bins from successive FFTs. The overlap of the data blocks causes these bins to be correlated, even when the noise is white. A simple expression is derived for the probability of false alarm when the covariance matrix of the FFT bins is tridiagonal     

The Correction of I and Q Errors in a Coherent Processor

A method is presented for correcting the gain and phase imbalances and the bias errors of the in-phase and quadrature channels of a coherent signal processor [1] by means of coefficients which are derived from measurements of a test signal. The residual errors after correction depend upon the signal-to-noise ratio (S/N) of the test signal and the degree of filtering used in deriving the correction coefficients.     

Optimum Active Array Processing Structure and Space-Time Factorability

An active array processor is concerned with the problem of detecting a signal echo, reflected from a target, in the presence of reverberation (clutter). The processor can also be used to estimate target range and bearing. It is a priori not evident whether the optimum (likelihood ratio) detector can be factored into spatial and temporal operations, thus resulting in a simpler processor implementation. This paper studies this problem for a linear continuous array in a reverberation-limited environment. Conditions on signal, reverberation, and array parameters are derived under which the optimum detector is factorable. The validity of using factorability as a criterion of signal design is briefly examined. Finally, the relationship between space-time factorability and range-bearing estimates is pointed out.     

基于龙芯处理器的系统移植方法和应用可行性研究

提出了基于龙芯计算模块的嵌入式操作系统移植和实现方法,实现了龙芯计算模块的操作系统加载、 启动和驱动开发,并介绍了龙芯处理器的性能测试方法和测试结果,为龙芯国产处理器在航空电子领域的部署 和应用可行性提供了一定的依据。     

Design and implementation for a digital synchronous reluctancedrive

A systematic controller design for a synchronous reluctance drive system is presented. This controller consists of two parts: a forward-loop H^∞ controller to improve the transient response, and a load compensator to reduce the load disturbance. Based on a simplified model of the drive system, a control algorithm has been derived. Detailed analysis of the characteristics of the closed-loop system is presented. The effects of the parameter variations are also studied. A digital signal processor, TMS-320-C30, is used to implement the control algorithm. Both the speed control and the position control of the drive system can be implemented by using the proposed control method. Furthermore, all the control loops are executed by the digital signal processor. The system, as a result, is very flexible. The whole drive system performs well although its hardware is very simple. For speed control, the system can be operated at a speed as low as 1 r/min. For position control, the system can accurately control a one-axis table. In addition, the system also has good position tracking ability. Several experimental waveforms validate the simulated results     

An Adaptive Array Signal Processing Algorithm for Communications

An algorithm is described for initial synchronization in a communication system with a digital adaptive array. This algorithm can also be used for message extraction. A set of consecutive complex video samples of the array output is processed to obtain optimum adaptive array weights, based on a least mean square (LMS) error criterion. This computation is performed for each of the possible alternative signals which may be present during an observation interval. The correct synchronization time or message symbol is selected as the one which yields the minimum LMS error. Assuming orthogonality of the alternative codes, a probability distribution for the output of this processor has been derived.     

Image Registration: Similarity Measure and Preprocessing Method Comparisons

An experimental comparison of several similarity measures and preprocessing techniques used for the registration of temporally differing images is carried out. It is found that preprocessing of the images via a gradient operator improves the registration performance. This is in agreement with a derived optimal processor (described in the Appendix) based upon image and temporal difference characteristics.     

Design and implementation of a robust controller for a synchronousreluctance drive

A robust controller design for a synchronous reluctance drive system is presented. Based on a simplified model of the system, a robust position controller has been derived. A digital signal processor (DSP), TNO-320-C30, is used to implement the control algorithm. Furthermore, all the current, velocity, and position control loops are executed by the DSP. The system, as a result, is very flexible. Although the hardware circuit of the system is very simple, the synchronous reluctance drive system can accurately control a one-axis table. In addition, the system also has good transient response, load disturbance response, and tracking ability. Several experimental results validate the theoretical analysis     

Hard-Limiter Output Autocorrelation Function: Gaussian & Sinusoidal Input

An expression is derived for the autocorrelation function of the output of a hard limiter whose input is stationary Gaussian noise with zero mean plus independent random-phase sinusoidal signal. The output spectrum may then be evaluated. This spectrum is extremely useful in understanding the properties of a filter-limit-filter-detect signal processor whose signal input is an actual sinusoid, or when a sinusoid is used as a test signal.     

A flexible processor for a digital adaptive array radar

A digital beamforming processor for an adaptive array radar is described. The functionality and the architecture of the processor are strongly driven by a goal of achieving adaptive null depths in the 60-dB to 70-dB range, which necessitates substantial preprocessing of each channel. In particular, conversion to baseband quadrature channels is accomplished digitally using a single A/D converter per channel, and FIR (finite impulse response) equalizing filters are employed in each channel to match channel transfer functions. The processor is highly modular, and this not only distributes the total processing load, but also the I/O (input/output) bandwidth requirement. This is accomplished by distributing the adaptive beamforming algorithm systolically across a linear array of processing nodes. The processor is expandable to a different number of channels and sufficiently flexible to be applied to other problems of an array signal processing nature. Experimental data presented demonstrate that the processor is capable of supporting channel-to-channel cancellation of interfering signals to the level of -65 dB     

多线程控制技术在面向对象实时仿真中的应用

随着实时仿真复杂性的提高,单个的处理器不足以完成所有的必需仿真计算任务。希望能在不同的处理器上完成实时仿真的不同任务,对称多处理器的机制需要软件支持,以使每个处理器通过共享内存进行信息交换。利用多线程控制技术,可以在非全进程开销或不使用共享内存的条件下,使用多处理器。其理由在于线程本身就蕴涵有共享地址的概念。一个多线程的实时程序,利用其中的主线程控制其它的辅助线程,每个处理器用于完成一个辅助的实时计算线程,主线程负责实时时钟的监控,当时钟到达时,启动相应的辅助线程,辅助线程利用图形用户界面(GUI)来监控仿真的进行。     

Computational Precision Requirements for Optimal Weights in Adaptive Processing

The required accuracy for computing the estimated optimum weights of an adaptive processor has been analyzed by investigating the effects of errors in computing the inverse matrix. It is shown that the required precision depends upon the matrix. An equation for the general case is derived. Several special cases are considered in detail. It is shown that the case of a single interference source requires the highest precision. The least stressing case is identifi'ed and compared to the worst case. The requirements for a "typical" case are also considered. A comparison of the requirements for the covariance matrix estimation technique and for adaptive weight implementation using gradient descent techniques is given. It is shown that there is a dichotomy in that cases that do not stress one technique tend to stress the other.     

Radar receiver optimization for a continuously scanning antenna

The optimum coherent radar receiver configuration is derived for a continuously scanning antenna on the basis of maximizing the available energy for a given processor complexity. Included in the analysis are the length of the coherent dwell, the size of the discrete Fourier transform and the degree of weighting used for Doppler filtering, and the use of overlapped processing windows. Gaussian shapes for the processing window and antenna mainbeam are assumed in order to make the analysis tractable     

Multipath Angle Error Reduction Using Multiple-Target Methods

The usual methods of reducing multipath angle errors in monopulse tracking radar achieve only limited success because they do not attack the root of the problem. A more correct approach is to accept the multipath signal as a second target and utilize a two-target signal processor which angle tracks both wavefronts. The processor will decouple the return signals so that relatively interference-free data on both waves are obtained. In this paper a signal processor for separating signal from (N - 1) multipath components is developed. The processor is then specialized to the case of only one multipath signal and evaluated by a computer simulation. Data show that large improvements are possible as compared to the usual monopulse tracking system. In particular, the usual large bias errors at low elevation angles are eliminated. Tracking precision compares favorably with the theoretically best possible for two-target tracking systems.     

Optimal time-varying load sharing for divisible loads

A load sharing problem involving the optimal load allocation of divisible loads in a distributed computing system consisting of N processors interconnected through a bus-oriented network is investigated. For a divisible lend, the workload is infinitely divisible so that each fraction of the workload can be distributed and independently computed on each processor. For the first time in divisible load theory, an analysis is provided in the case when the processor speed and the channel speed are time varying due to background jobs submitted to the distributed system with nonnegligible communication delays. A numerical method to calculate the average of the time-varying processor speed and the channel speed and an algorithm to find the optimal allocation of the workload to minimize the total processing finish time are proposed via a deterministic analysis. A stochastic analysis which makes use of Markovian queueing theory is introduced for the case when arrival and departure times of the background jobs are not known     

Synthetic Aperture Radar

The general theory of side-looking synthetic aperture radar systems is developed. A simple circuit-theory model is developed; the geometry of the system determines the nature of the prefilter and the receiver (or processor) is the postfilter. The complex distributed reflectivity density appears as the input, and receiver noise is first considered as the interference which limits performance. Analysis and optimization are carried out for three performance criteria (resolution, signal-to-noise ratio, and least squares estimation of the target field). The optimum synthetic aperture length is derived in terms of the noise level and average transmitted power. Range-Doppler ambiguity limitations and optical processing are discussed briefly. The synthetic aperture concept for rotating target fields is described. It is observed that, for a physical aperture, a side-looking radar, and a rotating target field, the azimuth resolution is ?/? where ? is the change in aspect angle over which the target field is viewed, The effects of phase errors on azimuth resolution are derived in terms of the power density spectrum of the derivative of the phase errors and the performance in the absence of phase errors.     

Equal allocation scheduling for data intensive applications

A new analytical model for equal allocation of divisible computation and communication load is developed. Equal allocation of load is attractive in multiple processor systems when real time information on processor and link capacity that is necessary for optimal scheduling is not available. The model includes a detailed accounting of solution reporting time. Equal allocation scheduling is compared with sequential scheduling and a new type of multi-installment scheduling. Aerospace applications include the processing of satellite imagery, radar, and sensor networks.