Performance of a Square Law Pseudonoise Ranging Time-of-Arrival Estimator

The performance of a square law time-of-arrival (TOA) estimator that has been proposed for use in ASTRO-DABS, part of a possible satellite-based fourth generation air traffic control system is considered. The transmitted message consists of a pulse amplitude modulated (PAM) ranging sequence that, due to transmitter characteristics, is corrupted by an unknown frequency offset. The optimum TOA estimator, for the case of no frequency uncertainty, is first presented, together with a lower bound on the variance of the estimate generated. This is followed by the consideration of a suboptimum TOA estimator for which a high signal-to-noise ratio (SNR) performance analysis is carried out; here, the effects of frequency uncertainty are included. Next, the zero-crossing properties of the derivative of the (suboptimum) estimation statistic are presented and the results used to derive an upper bound to the TOA estimate variance that is valid for all SNR values. This latter result is significant because it displays the system threshold effect and complements performance lower bounds that may be derived via other methods. In addition, the method presented here may be applied to other optimum and suboptimum systems where a discrete set of parameters is to be estimated.     

Second-order acceleration models for an MMAE target tracker

The performance of a multiple model adaptive estimator (MMAE) for an enhanced correlator/forward-looking-infrared tracker for airborne targets is analyzed in order to improve its performance. Performance evaluation is based on elemental filter selection and MMAE estimation error sizes and trends. The elemental filters are based on either first or second-order acceleration models. Improved filter selection is achieved by using acceleration models that separate the frequency content of acceleration power spectral densities into non-overlapping regions with second-order models versus the more traditional overlapping regions with first-order models. A revised tuning method is presented. The maximum a posteriori (MAP) versus the Bayesian MMAE is investigated. The calculation of the hypothesis probability calculation is altered to see how performance is affected. The impact of the ad hoc selection of a lower bound on the elemental filter probability calculation to prevent filter lockout is evaluated. Parameter space discretization is investigated     

A novel multistage estimation of signal parameters

A multistage estimation scheme is presented for estimating the parameters of a received carrier signal possibly phase-modulated by unknown data and experiencing very high Doppler, Doppler rate, etc. Such a situation arises, for example, in the case of the Global Positioning Systems (GPS). In the proposed scheme, the first-stage estimator operates as a coarse estimator of the frequency and its derivatives, resulting in higher RMS estimation errors but with a relatively small probability of the frequency estimation error exceeding one-half of the sampling frequency (an event termed cycle slip). The second stage of the estimator operates on the error signal available from the first stage, refining the overall estimates, and in the process also reduces the number of cycle slips. The first-stage algorithm is a modified least-squares algorithm operating on the differential signal model and referred to as differential least squares (DLS). The second-stage algorithm is an extended Kalman filter, which yields the estimate of the phase as well as refining the frequency estimate. A major advantage of the proposed algorithm is a reduction in the threshold for the received carrier power-to-noise power spectral density ratio (CNR) as compared with the threshold achievable by either of the algorithms alone     

论加速可靠性增长试验 (Ⅶ )步进应力试验方案的统计分析

对幂律-线性化模型步进应力加速可靠性增长试验方案，给出了模型参数，加速系数及MTBF的极大似然估计，极大后验估计，Bayes估计及其计算方法，对这些方案给出了Monte Carlo模拟方法，并用数值例说明了这些方法。     

Implementation of nondeterministic pulsewidth modulation forinverter drives

A single-phase power factor preregulator to improve the power quality in the input side of an ac/dc/ac converter and a random pulsewidth modulation (PWM) to reduce the emitted noise energy and the mechanical vibration for an induction motor drive is proposed. The hysteresis current control (HCC) technique for a voltage source switching mode rectifier (SMR) is adopted. A control scheme is presented such that the line current is driven to follow the reference current which is derived from the dc bus voltage regulator and the output power estimator. A random pulse position technique for a three-phase voltage source inverter system to reduce the noise energy and resonant vibration from ac machine drive is described. By randomly varying the instantaneous pulse position in each switching frequency, the frequency distribution of harmonics is spread in a wide frequency range which results in reduction of torque pulsations in the ac motor drive systems. To investigate the proposed control scheme, experimental tests based on a laboratory prototype were implemented to show the nearly unity power factor at the SMR and reduce the noise energy concentrated at the specific tones     

On Signal and Noise Level Estimation in a Coherent PCM Channel

Joint maximum likelihood estimators are presented for the signal amplitude and noise power density in a coherent PCM channel with white Gaussian noise and a correlation receiver. The estimates are based upon the correlation coefficient outputs of the receiver. From these estimators, an estimator for the quantity (received signal energy)/bit/,(noise power)/(unit bandwidth) upon which the error probabilities depend, is derived. This estimator is shown to be useful as 1) a point estimator for the signal-to-noise ratio for the higher values of this ratio (about 4 dB or greater), and 2) an easily calculated statistic upon which to base data acceptance or rejection criteria. The acceptance or rejection levels are obtained by the use of confidence interval curves in conjunction with word error probability data.     

一种频域插值变化迭代频率估计方法

针对现有频率估计算法存在的复杂度高、频率估计能力弱、估计结果均方差大等缺点,在固定迭代AM（Aboutanios—Mulgrew）无偏频率估计算法基础上,提出一种频域插值变化迭代频率估计算法,推导了不同迭代参数实现无偏估计的充分条件,证明了有偏估计时本算法的收敛性和偏离度,通过设置不同迭代参数,可以实现无偏或有偏估计。仿真分析表明：当具有较高信噪比时,在整个频率估计范围内,该方法均方误差接近CRLB（Cramer-RaoLowerBound,克拉美一罗下限）;当FFT（FastFourierTransform,快速傅里叶变换）粗估计残余频率接近0．5时,该方法的均方误差优于CRLB,为CRLB的96％。     

Angle of arrival estimation of coherent signals using an arraydoublet in motion

Shown here is how the estimation of signal parameters via relational invariance techniques (ESPRIT) algorithm may be used with a single pair of antennas in motion to estimate angles of arrival (AOA) for coherent signals. The approach exploits the Doppler frequency shifts caused by the doubler in motion. With this estimator, the number of signals that can be handled is not limited by the size of the array, as in the usual ESPRIT application, but by an adjustable parameter. A theoretical performance analysis of the estimator and typical examples showing the use of this estimator are given     

宽带信号近似最大似然方位估计快速算法

 针对短采样宽带信号近似最大似然方位估计（AML）计算量大的问题,将马尔可夫蒙特卡罗(MCMC)方法与近似最大似然方位估计相结合,提出一种基于完美抽样的近似最大似然方位估计快速算法（PAML）。该算法将AML算法的空间谱函数作为信号的概率分布函数,并利用完美抽样方法从该概率分布函数中抽样。与AML和遗传算法的对比实验研究表明,两目标情况下PAML算法在中低信噪比条件下的估计性能与AML和遗传算法性能相当,而计算量分别是二者的1/24和1/3。随着目标个数的增加,PAML算法的计算量优势将更加明显。     

Orbital reference frame estimation with power spectral density constraints for drag-free satellites

The drag-free satellites are widely used in the field of fundamental science as they enable the high-precision measurement in pure gravity fields. This paper investigates the estimation of local orbital reference frame (LORF) for drag-free satellites. An approach, taking account of the combi-nation of the minimum estimation error and power spectral density (PSD) constraint in frequency domain, is proposed. Firstly, the relationship between eigenvalues of estimator and transfer func-tion is built to analyze the suppression and amplification effect on input signals and obtain the eigenvalue range. Secondly, an optimization model for state estimator design with minimum estima-tion error in time domain and PSD constraint in frequency domain is established. It is solved by the sequential quadratic programming (SQP) algorithm. Finally, the orbital reference frame estimation of low-earth-orbit satellite is taken as an example, and the estimator of minimum variance with PSD constraint is designed and analyzed using the method proposed in this paper.     

Low observable target motion analysis using amplitude information

In conventional passive and active sonar system, target amplitude information (AI) at the output of the signal processor is used only to declare detections and provide measurements. We show that the AI can be used in passive sonar system, with or without frequency measurements, in the estimation process itself to enhance the performance in the presence of clutter where the target-originated measurements cannot be identified with certainty, i.e., for “low observable” or “dim” (low signal-to-noise ratio (SNR)) targets. A probabilistic data association (PDA) based maximum likelihood (ML) estimator for target motion analysis (TMA) that uses amplitude information is derived. A track formation algorithm and the Cramer-Rao lower bound (CRLB) in the presence of false measurements, which is met by the estimator even under low SNR conditions, are also given. The CRLB is met by the proposed estimator even at 6 dB in a cell (which corresponds to 0 dB for 1 Hz bandwidth in the case of a 0.25 Hz frequency cell) whereas the estimator without AI works only down to 9 dB. Results demonstrate improved accuracy and superior global convergence when compared with the estimator without AI. The same methodology can be used for bistatic radar     

A novel control method for turboshaft engine with variable rotor speed based on the Ngdot estimator through LQG/LTR and rotor predicted torque feedforward

In order to compensate for the disturbance of wide variation in rotor demanded torque on power turbine speed and realize the fast response control of turboshaft engine during variable rotor speed, a cascade PID control method based on the acceleration estimator of gas turbine speed (Ngdot) and rotor predicted torque feedforward is proposed. Firstly, a two-speed Dual Clutch Transmission (DCT) model is applied in the integrated rotor/turboshaft engine system to achieve variable rotor speed. Then, an online estimation method of Ngdot based on the Linear Quadratic Gaussian with Loop Transfer Recovery (LQG/LTR) is proposed for power turbine speed cascade control. Finally, according to the cascade PID controller based on Ngdot estimator, a rotor demanded torque predicted method based on the Min-batch Gradient Descent-Neural Network (MGD-NN) is put forward to compromise the influence of rotor torque interference. The simulation results show that compared with cascade PID controller based on Ngdot estimator and the one combined with collective pitch feedforward control, the novel control method proposed can reduce the overshoot of power turbine speed by more than 20%, which possesses faster response, superior dynamic effect and satisfactory robustness performance. The control method proposed can realize the fast response control of turboshaft engine with variable rotor speed better.     

Multiple-model estimation with variable structure. III. Model-groupswitching algorithm

A general multiple-model (MM) estimator with a variable structure (VSMM), railed model-group switching (MGS) algorithm, is presented. It assumes that the total set of models can be covered by a number of model groups, each representing a cluster of closely related system behavior patterns or structures, and a particular group is running at any given time determined by a hard decision. This algorithm is the first VSMM estimator that is generally applicable to a large class of problems with hybrid (continuous and discrete) uncertainties. It is also easily implementable. It is illustrated, via a simple fault detection and identification example, that the MGS algorithm provides a substantial reduction in computation while having identical performance with the fixed-structure Interacting Multiple-Model (FSIMM) estimator     

DOA estimation under unknown mutual coupling and multipath

We propose a new method for direction of arrival (DOA) estimation in the presence of multipath propagation and mutual coupling for a frequency hopping (FH) system. With the use of pilot symbols and assuming perfect time-frequency synchronization for a linear array, we take mutual coupling and multipath propagation into account, and derive a maximum likelihood (ML) estimator for both the mutual coupling matrix and DOA estimation. We then formulate an iterative alternating minimization (AM) algorithm for finding the mutual coupling and DOA parameters in an alternate manner. Simulation results illustrating the performance of the algorithm and comparison with the Cramer-Rao bound (CRB) are also presented.     

Optimal CFAR detection in Weibull clutter

Optimal, in the maximum likelihood sense, constant false-alarm rate (CFAR) detection for Weibull clutter statistics, is investigated. The proposed OW (optimal Weibull) estimator is proved to be an asymptotically efficient estimator of the mean power of the Weibull clutter. Theoretical analysis of the OW-CFAR detector is provided, while detection performance analysis is carried out using the Monte Carlo simulation method. The operation of the median and morphological (MEMO)-CFAR detector in Weibull clutter statistics is also explained. It performs almost optimally in uniform clutter and, simultaneously, it is robust in multitarget situations. The performance of the proposed OW-CFAR detector in uniformal Weibull clutter is used as a yardstick in the analysis of the MEMO cell-averager (CA) and ordered statistic (OS) CFAR detectors. Nonfluctuating and fluctuating (Swerling II) targets are considered in detection analysis. The performance of the detectors is also examined at clutter edges     

A simple fixed-lag algorithm for tracking frequency rate-of-change

A family of simple fixed-lag frequency smoothing algorithms which provide good estimates of both frequency and frequency rate-of-change is reported. The smoothers were developed from a fixed-gain αβ tracker by replacing the recursive derivative estimator with a finite-impulse-response (FIR) differentiator. Simulation results are presented which show that the smoothing algorithms provide frequency estimates with a similar variance to those produced by the αβ filter but with greatly improved frequency-rate estimates. The smoothing algorithms and the αβ filter are also compared on the basis of the bias and delay introduced in the frequency-rate estimates. Although the results presented are for frequency estimation, the smoothing algorithms can be used in any single-input tracking application where some lag in the estimates is allowable     

Radar power multiplier for acquisition of low observables using anESA radar

In this paper the acquisition of a low observable (LO) incoming tactical ballistic missile using the measurements from a surface based electronically scanned array (ESA) radar is presented. We present a batch maximum likelihood (ML) estimator to acquire the missile while it is exo-atmospheric. The proposed estimator, which combines ML estimation with the probabilistic data association (PDA) approach resulting in the ML-PDA algorithm to handle false alarms, also uses target features. The use of features facilitates target acquisition under low signal-to-noise ratio (SNR) conditions. Typically, ESA radars operate at 13-20 dB, whereas the new estimator is shown to be effective even at 4 dB SNR (in a resolution cell, at the end of the signal processing chain) for a Swerling III fluctuating target, which represents a significant counter-stealth capability. That is, this algorithm acts as an effective “power multiplier” for the radar by about an order of magnitude. An approximate Cramer-Rao lower bound (CRLB), quantifying the attainable estimation accuracies and shown to be met by the proposed estimator, is derived as well     

Frequency estimation techniques for high dynamic trajectories

A comparison is presented of four different estimation techniques applied to the problem of continuously estimating the rapidly varying parameters of a sinusoidal signal, observed in the presence of additive noise. Frequency estimates are emphasized, although phase and/or frequency rate are also estimated by some of the algorithms. These parameters are related to the velocity, position, and acceleration of the maneuvering receiver or transmitter. Estimated performance at low carrier-to-noise ratios and high dynamics is investigated for the purpose of determining the useful operating range of an approximate maximum likelihood estimator, an extended Kalman filter, a cross-product automatic frequency loop and a phase-locked loop. Numerical simulations are used to evaluate performance while tracking a common trajectory exhibiting high dynamics     

Precision large scale air traffic surveillance using IMM/assignmentestimators

We present the development and implementation of a multisensor-multitarget tracking algorithm for large scale air traffic surveillance based on interacting multiple model (IMM) state estimation combined with a 2-dimensional assignment for data association. The algorithm can be used to track a large number of targets from measurements obtained with a large number of radars. The use of the algorithm is illustrated on measurements obtained from 5 FAA radars, which are asynchronous, heterogeneous, and geographically distributed over a large area. Both secondary radar data (beacon returns from cooperative targets) as well as primary radar data (skin returns from noncooperative targets) are used. The target IDs from the beacon returns are not used in the data association. The surveillance region includes about 800 targets that exhibit different types of motion. The performance of an IMM estimator with linear motion models is compared with that of the Kalman filter (KF). A number of performance measures that can be used on real data without knowledge of the ground truth are presented for this purpose. It is shown that the IMM estimator performs better than the KF. The advantage of fusing multisensor data is quantified. It is also shown that the computational requirements in the multisensor case are lower than in single sensor case, Finally, an IMM estimator with a nonlinear motion model (coordinated turn) is shown to further improve the performance during the maneuvering periods over the IMM with linear models     

Direction finding with a four-element Adcock-Butler matrix antennaarray

The conventional analog Adcock-Butler matrix (ABM) antenna array direction finder suffers from systemic errors, component matching problems, and bandwidth limitations. Three digital bearing estimators are developed as candidates to replace the analog signal processing portion of the ABM. Using the same antenna array, they perform all signal processing in the frequency domain, thereby benefitting from the computational efficiency of the fast Fourier transform (FFT) algorithm. The first estimator requires two analog-to-digital converters (A-D) and three antenna elements. It multiplies the difference between the discrete Fourier transforms (DFTs) of the output signals from two antenna elements with that from a third antenna element. At each frequency component, the phase of this product is a function of the bearing. A weighted least squares (LS) fit through all the phase components then gives a bearing estimate. The second estimator is similar to the first but uses three A-D and all four antenna elements. The output signal from the additional antenna element provides an independent estimate of the weights for the LS fit, giving an improvement in accuracy. The third estimator applies the physical constraint existing between the time-difference-of-arrival (TDOA) of a signal intercepted by two perpendicular sets of antenna elements. This yields a better estimator than simple averaging of the bearing from each set of antenna elements. The simulation studies used sinusoids and broadband signals to corroborate the theoretical treatment and demonstrate the accuracy achievable with these estimators. All three direction finders have superior performance in comparison with the analog ABM