A hardware-efficient, multirate, digital channelized receiverarchitecture

An approach is presented to realizing a digital channelized receiver for signal intercept applications that provides a hardware efficient implementation of a uniform filter bank in which the number of filters K is greater than the decimation factor M. The proposed architecture allows simple channel arbitration logic to be used and provides reliable instantaneous frequency measurements, even in adjacent channel crossover regions. In the proposed implementation of the filter bank, K is related to M by K=FM where F is an integer. It is shown that the optimum selection of F allows the instantaneous frequency measurement to be made in the channel crossover region and the arbitration function to be based solely on the instantaneous frequency measurement. The development of a filter bank structure which combines the flexibility of the short-time Fourier transform (STFT) with the implementation efficiency of the polyphase filter bank decomposition, meeting these requirements and leading to a hardware-efficient implementation, is presented     

A digital quadrature demodulation system

Existing digital quadrature demodulation techniques sample the input at either 2B Hz or 4B Hz, select the even samples as the in-phase (I), and interpolate the odd samples to give the quadrature (Q), output. The signal bandwidth is B. We propose a demodulation system to produce I and Q samples at arbitrary sampling rate greater than 2B Hz. The system eliminates the IF downconversion step with a special sampling scheme. The even samples correspond to the I component, while the Q components are the filtered output. The filter can be a lowpass or least squares (LS) filter. The lowpass filter design is based on trade-offs between the filter length and the degree of oversampling. It produces similar results as previous work when the sampling rate is 2B Hz or 4B Hz. Unlike existing methods which assume the input is white, a LS filter, on the other hand, can make use of input signal characteristics to achieve a better result. The higher the correlation in the input the larger the improvement. The cost for LS filtering is a coefficient update step if the input is time varying. A scheme to cancel dc offset from analog to digital (A/D) converters is also given     

The effect of I,Q mismatch errors on adaptive cancellation

The effects of in-phase (I) and quadrature-phase (Q) amplitude errors and low-pass-filter (LPF) errors on adaptive cancellers are investigated. I,Q errors occur because of errors in the synthesis process of the mixers and LPFs designed to be identical for each input channel. These I,Q errors among the channels result in cancellation degradation. Tapped delay line transversal filters have been proposed as a way to compensate for these errors and thus improve cancellation performance. However, it is shown that if there is any LPF mismatch, then transversal filtering has a small effect on improving canceler performance. The use of individual I,Q adaptive transversal filter weighting is suggested as a means of completely eliminating the phase amplitude errors, and making the canceler performance responsive to transversal filter compensation     

Noncoherent Detection of Split-Phase FSK by Multiple Predetection Filtering

When the cumulative drift in the center frequency of a binary split-phase FSK signal exceeds the peak deviation of the signal, a conventional noncoherent receiver (i.e., one provided with only two IF filters) may be unable to achieve the probability of error per bit which the designer desires. This limitation may be overcome if the receiver is provided with a bank of more than two contiguous filters (each followed by an envelope detector) tospan the total IF band the instantaneous IF signal might occupy. It is shown that the probability of error per bit for such a receiver is a function of 1) the ratio F of peak frequency deviation to peak frequency drift, 2) the number M of IF filter/detectors, and 3) the signal-to-noise ratio ? in the output of the filter containing the signal. It is further shown thatfor a given value of F an increase in M reduces the amount of transmitter power the communication system designer must provide to yield a given probability of error per bit.     

Real-Time Motion Desmearing of Airborne Imagery

This paper considers the real-time ?desmearing? of motion- ?smeared? imagery telemetered from an airborne platform. The specific configuration considered is the direct raster scan readout of a satellite-mounted vidicon. Three types of smearing are considered: 1) linear uniform smearing, 2) linear nonuniform smearing, and 3) nonlinear smearing. The simplest type of smearing, linear uniform, has as its desmearing or inverse filter a circulating delay line (CDL) cascaded with a differentiator. An error analysis of this filter is presented along with an experimental simulation. Linear, non-uniform smearing characterized by the operator begin{equation*}int^{t}_{t-delta(t)}I(tau){ }{dtau}end{equation*} is considered next. Two possible realizations for the inverse filter are discussed as to accuracy and practicality. Finally, an error analysis is performed for the nonlinear smearing that results from a skewing of the raster scan.     

基于MSP430汽车防抱死制动控制器的设计

介绍了一种汽车防抱死制动系统控制器的设计。控制器以MSP430F149单片机为核心,根据防抱死制动系统的工作原理,利用轮速传感器,对轮速进行滤波、放大、整形等实现车轮速度的采集。采用基于车轮滑移率的防抱控制理论,根据车速、轮速来计算车轮滑移率。在硬件设计方面,根据系统选择了MSP430F149单片机,设计出信号输入回路、输出驱动回路、电源部分,给出了系统结构原理图。     

电流积分器对I/F转换性能的影响分析

本文介绍了带分流结构的电流/频率转换电路和电流积分器的工作原理,推导了电流积分器的误差,并分析了运放的几个关键参数对l/F电路性能的影响.通过理论推导和实验对比,得出了I/F电路设计时电流积分器电路选择运算放大器的参考依据,并对带分流结构的I/F电路作出了改进.     

磁致伸缩材料作动器用于主动振动控制的实验研究

对采用磁致伸缩材料作动器进行主动振动控制的问题进行了实时实验研究。首先简介了磁致伸缩材料作动器的设计和特性分析及自适应滤波算法(LMS)的基本原理;然后论述了采用磁致伸缩材料作动器的单自由度主动振动控制实验的系统,从不同的控制物理量、不同算法、偏置磁场和系统噪声等方面分析了影响控制效果的因素,实验获得了30dB的减振效果。      

Multipath-adaptive GPS/INS receiver

Multipath interference is one of the contributing sources of errors in precise global positioning system (GPS) position determination. This paper identifies key parameters of a multipath signal, focusing on estimating them accurately in order to mitigate multipath effects. Multiple model adaptive estimation (MMAE) techniques are applied to an inertial navigation system (INS)-coupled GPS receiver, based on a federated (distributed) Kalman filter design, to estimate the desired multipath parameters. The system configuration is one in which a GPS receiver and an INS are integrated together at the level of the in-phase and quadrature phase (I and Q) signals, rather than at the level of pseudo-range signals or navigation solutions. The system model of the MMAE is presented and the elemental Kalman filter design is examined. Different parameter search spaces are examined for accurate multipath parameter identification. The resulting GPS/INS receiver designs are validated through computer simulation of a user receiving signals from GPS satellites with multipath signal interference present The designed adaptive receiver provides pseudo-range estimates that are corrected for the effects of multipath interference, resulting in an integrated system that performs well with or without multipath interference present.     

U-D分解的固定点平滑新算法及其在飞行试验中的应用

 本文根据Rauch固定点平滑公式,提出了一种U-D分解的固定点平滑新算法。这一算法不仅具有良好的数值稳定性和可靠性,而且计算量较少;计算效率是Bryson-Ho Y C固定点平滑计算效率的1.5倍以上。将这种新算法用于飞机运动状态初值的确定,提高了飞机气动参数辨识精度。     

Intelligent SINS/RDSS Integrated Algorithms for Land Vehicle Navigation

This is a discussion of the design of strap-down inertial navigation systems (SINS) and radio determination satellite service (RDSS) integrated navigation algorithms. The research aims at testing the effectiveness of artificial intelligence (AI)-aided Kalman filtering (KF) approaches for land vehicle applications. A back-propagation neural network (BPNN)-aided K*F algorithm and a fuzzy inference-based KF algorithm are presented in order to overcome the time delay of RDSS positioning provided by a double-star positioning system in China. Traditional KF causes biased solutions, and indeed, leads to filter instability easily since the time delay of RDSS positioning, in an active mode, is hard to be modeled and sometimes suffers from RDSS outages. Therefore, a fuzzy inference is used to correct the variance matrix of KE measurement noises adaptively; and a trained BPNN corrects the outputs of the Kalman filter. The algorithms proposed herein have been verified on real SINSIRDSS data. collected in land vehicle tests and are compared with other approaches. The results demonstrate that fuzzy inference-based KF algorithms improve the positioning accuracy to over 40 % better than KF algorithms, and BPNN-aided KF algorithms have the same precision as GPS which is the reference station In dynamic experiments without RDSS outages. The test results with RDSS outages indicate that the fuzzy inference-based KF is feasible but with positioning errors of hundreds of meters, so the BPNN-aided KF is designed to efficiently compensate for RDSS outages and improve system performance.     

The Performance of Analog Correlators for Several Integrator Functions

A measure of analog correlator performance is considered and interpreted reted as an output signl-to-noise ratio. This quantity is shown to depend on the fourth-order expectation of the input signals and the characteristics of the integrating system. Based on the output signal-to-noise ratio, figures of merit are established for correlators utilizing an ideal low-pass filter, an RC filter, and a finite time integrator. These figures of merit indicate to what degree the correlators reject noise components. For jointly Gaussian inputs, the variation of the output signal-to-noise ratio with the input signal-to-noise ratio is shown to be independent of the integrating system. Finally, a graphical comparison indicates the characteristics of the three systems for several different parameters. This comparison shows that the finite time integrator is superior to the other two systems considered.     

单恒流源电流频率转换技术研究

本文设计了一种单恒流源电流频率转换电路,使电路的功耗减小一半,更加小型化,并且具有更好的对称性和精度.提出并从原理上论证了这种单恒流源I/F技术的理论依据,设计出相应的硬件电路,验证其原理的正确性和工程上的可行性.为单恒流源I/F技术的研发,拓展了思路,奠定了基础.     

Interacting multiple model filter for tactical ballistic missile tracking

An interacting multiple model (IMM) filter is presented for the real-time tracking of tactical ballistic missiles (TBMs). The novel aspects of the proposed IMM filter include the development of a constant axial force (CAF) Kalman filter, asymmetric IMM state interaction, and an entropy-based variation of the IMM mode probability update equation. Using data from a recent TBM defense (TBMD) test event, the proposed IMM filter is shown to yield consistent state estimates throughout the entire TBM trajectory, which includes a dual-stage boost during launch.     

幅度及多普勒信息辅助的多目标跟踪算法

针对现有的多目标跟踪（MTT）算法在强杂波环境下会出现严重的性能衰退,利用目标的幅度及多普勒特征,基于随机有限集（RFS）理论,提出了一种幅度及多普勒信息辅助的δ广义标签多伯努利（ADI-δ-GLMB）滤波器。首先,利用幅度及多普勒信息对目标状态进行扩展,在此基础上建立了新的量测似然函数。然后,基于δ-GLMB滤波器框架推导了新的更新方程。最后,进行仿真验证,结果表明：强杂波下,ADI-δ-GLMB滤波器跟踪性能明显优于δ-GLMB滤波器,估计精度及稳定性更高,且计算量更低;同信息辅助的概率假设密度（PHD）、多目标多伯努利（MeMBer）滤波器相比,ADI-δ-GLMB滤波器状态估计精度更高。     

自适应高阶容积卡尔曼滤波在目标跟踪中的应用

针对传统容积卡尔曼滤波(CKF)在系统状态发生突变时估计精度下降的问题,将强跟踪滤波(STF)算法与高阶容积卡尔曼滤波(HCKF)算法相结合,提出了一种自适应高阶容积卡尔曼滤波(AHCKF)方法。该算法采用高阶球面-相径容积规则,可获得高于传统CKF的估计精度,同时在HCKF算法中引入STF,通过渐消因子在线修正预测误差协方差阵,强迫残差序列正交,提高了算法的鲁棒性,增强了算法应对系统状态突变等不确定因素的能力。将提出的AHCKF算法应用于具有状态突变的机动目标跟踪问题并进行数值仿真,仿真结果表明,AHCKF算法在系统状态发生突变的情况下表现出良好的滤波性能,有效地避免了状态突变造成的滤波精度下降,较传统的CKF、HCKF、交互式多模型-容积滤波(IMM-CKF)和自适应容积卡尔曼滤波(ACKF)算法有更强的鲁棒性和系统自适应能力。     

基于随机有限集的空间碎片群运动状态估计

传统的空间目标监测是建立在单目标状态估计基础之上,在面对突发产生的大量空间碎片时,由于碎片尺寸小,且密集分布以"群"的方式出现,传统单目标处理方法很难奏效。以"群"整体作为处理对象,基于随机有限集(RFS)技术,对"群"的状态特征进行估计。为了解决漏检目标密度分配问题和轨迹关联问题,提出一种面向量测的改进集势概率假设密度(CPHD)滤波器,并结合滤波后的信息处理过程,完成了对低轨空间碎片群的目标密度分布、群内目标数以及群内显著目标的状态估计。在仿真实验中,提出的滤波器表现明显优于传统滤波器和标准CPHD滤波器,且在某些传统滤波器和标准CPHD滤波器已失效的情况下,所提技术仍能有效工作。     

Adaptive Two-Stage Extended Kalman Filter for a Fault-Tolerant INS-GPS Loosely Coupled System

The well-known conventional Kalman filter requires an accurate system model and exact stochastic information. But in a number of situations, the system model has an unknown bias, which may degrade the performance of the Kalman filter or may cause the filter to diverge. The effect of the unknown bias may be more pronounced on the extended Kalman filter (EKF), which is a nonlinear filter. The two-stage extended Kalman filter (TEKF) with respect to this problem has been receiving considerable attention for a long time. Recently, the optimal two-stage Kalman filter (TKF) for linear stochastic systems with a constant bias or a random bias has been proposed by several researchers. A TEKF can also be similarly derived as the optimal TKF. In the case of a random bias, the TEKF assumes that the information of a random bi?s is known. But the information of a random bias is unknown or partially known in general. To solve this problem, this paper proposes an adaptive two-stage extended Kalman filter (ATEKF) using an adaptive fading EKF. To verify the performance of the proposed ATEKF, the ATEKF is applied to the INS-GPS (inertial navigation system-Global Positioning System) loosely coupled system with an unknown fault bias. The proposed ATEKF tracked/estimated the unknown bias effectively although the information about the random bias was unknown.     

Capacitive-loaded push-pull parallel-resonant converter

Results of a theoretical and experimental investigation of a capacitive-loaded push-pull parallel-resonant DC-DC converter (CL-PPRC) are presented and discussed. The push-pull parallel-resonant converter (PPRC) is driven by a lower-than-resonance frequency and the secondary voltage is rectified and smoothed by a capacitive filter. The CL-PPRC is shown to operate in the zero voltage switching (ZVS) mode with a boost-like DC transfer ratio that is approximately linear with the period of the switching frequency. Experimental results of a 180 W, high output voltage (1.8 KV) prototype are found to be in good agreement with the analysis, models, and simulation results presented. The basic characteristic of ZVS, the fact that the resonant current is passing through the switches only during a fraction of the period, the high-voltage transfer ratio, and the inherent input/output (I/O) isolation, make the proposed topology a viable design alternative in avionic and aerospace applications     

Unscented粒子滤波在静基座捷联惯导系统大方位失准角初始对准中的应用研究

 静基座大方位失准角的捷联惯导系统误差方程是非线性的,Unscented粒子滤波从非线性系统状态向量概率分布出发,结合Unscented卡尔曼滤波和粒子滤波的特点,无需对非线性系统模型进行处理而能达到较高的滤波精度。本文对Unscented粒子滤波进行了研究,并结合重采样算法,运用于捷联惯导系统静基座大方位失准角初始对准中,计算结果验证了该方法的有效性与优越性。