Comments on `Tracking a maneuvering target using input estimation''

P.L. Boglar (see ibid., vol.AES-23, no.3, p.298-310, May 1987) developed a recursive formulation of the Chan, Hu, and Plant (CHP) algorithm, and the results of the simulation verified the performance improvements. The commenter claims that Bogler obtained an incorrect recursive formulation of input estimation because he incorrectly used the formulation of the Kalman filter. The commenter presents calculations that aim to demonstrate this claim     

Augmenting the Linear Variance Equation

A technique is developed to convert the covariance analysis ofcertain time-varying linear systems into time-invariant form, thusallowing an arbitrary time step for the solution of the differentialequations. The result is accomplished by augmenting the linearvariance equation and augmenting the state vector if necessary. Themethod is illustrated with an example showing the covariancepropagation of ring laser gyro errors in a strapdown inertial systeminto navigation errors during turns.     

Carrier Tracking by Smoothing Filter Improves Symbol SNR

The potential benefit of using a smoothing filter to estimate a carrier phase over use of phase-locked loops (PLL) is determined. Numerical results are presented for the performance of three possible configurations of an all-digital coherent demodulation receiver. These are residual carrier PLL, sideband-aided residual carrier PLL, and finally sideband aided with Kalman smoother. The average symbol SNR after losses due to carrier phase estimation is computed for different total power SNRs, symbol rates, and symbol SNRs. It is found that smoothing is most beneficial for low symbol SNRs and low symbol rates. Smoothing gains up to 0.7 dB over sideband-aided residual carrier PLL, and the combined benefit of smoothing and sideband aiding relative to residual carrier loop is often in excess of 1 dB.     

Instrument Failure Detection in Partially Observable Systems

Instrument failure detection using the dedicated observer scheme (DOS) depends on partial state observability through each instrument which is monitored. For instrument fault detection by the DOS technique, a quantitative measure of partial state observability is established for each instrument and used to determine a necessary condition on the output structure of the system. This measure, called the internal redundancy of the instrument, indicates the complexity of the logic required for failure detection, and it also indicates where some hardware redundancy can be introduced into the system to improve the fault detection capability of the DOS. The principles developed are applied to a simulation of the pitch axis autopilot of the A7 jet aircraft.     

Adaptive Tracking Filter for Maneuvering Targets

A general method of continually restructuring an optimum Bayes-Kalman tracking filter is proposed by conceptualizing a growing tree of filters to maintain optimality on a target exhibiting maneuver variables. This tree concept is then constrained from growth by quantizing the continuously sensed maneuver variables and restricting these to a small value from which an average maneuver is calculated. Kalman filters are calculated and carried in parallel for each quantized variable. This constrained tree of several parallel Kalman filters demands only modest om; puter time, yet provides very good performance. This concept is implemented for a Doppler tracking system and the performance is compared to an extended Kalman filter. Simulation results are presented which show dramatic tracking improvement when using the adaptive tracking filter.     

Measurement of Distributed Targets with the Random Signal Radar

A model of a distributed target as a collection of independent, Poisson distributed point scatterers or scattering centers in a range-velocity target space is introduced and is characterized by a deterministic function called the ?scatterer density function.? This function is the density of the point scatterers in the range-velocity space and can be estimated in a relatively straightforward manner by any radar having adequate resolution in both range and velocity and no ambiguities in the region occupied by the distributed target. The use of the random signal radar with a correlator receiver is considered here and the statistical properties of the correlator output, when the return signal is from a distributed target, are derived. It is shown that the spectral density is simply related to the scatterer density function. The technique is illustrated by an example in which the target is a tornado modeled as a cylinder with constant angular velocity. The example suggests that is a possible to remotely estimate the radar cross section per unit volume as a function of distance from the center of the tornado.     

A Closely Regulated TWT Converter

The design concept for the traveling wave tube amplifier converter for possible use in the Thermoelectric Outer Planet Spacecraft (TOPS) is presented. An unusual combination of semiconductors and magnetics were utilized to achieve very stable voltage regulation on a number of separate outputs to satisfy the requirements of a high-power traveling wave tube (TWT), and at the same time operate at an efficiency of better than 90 percent from a 30-volt source. The circuitry consists of an output filter, an auxiliary Jensen oscillator driving a high-reactance transformer to provide current limiting to the heater, a variable time delay, a main Jensen oscillator driving the power transformer with a maximum step-up ratio of 120 to 1, and series transistorized post regulators to provide precise voltage adjustment and low output impedance. This paper discusses the design of the high-reactance transformer and the high step-up ratio transformer, as well as the high-voltage series regulators that are limited in range and operate at the top of the unregulated output voltage. Test data is presented, and details of current transients caused by charging the filter circuits, input current ripple, and output voltage ripples are considered. The circuit provides better than 0.5 percent regulation against load change, input voltage change, and over-operating temperature range of from -20 to + 80°C, with output ripple voltage of less than 2 volts peak-to-peak on top of the 3600-Vdc output. The measured efficiency was typically 87 percent. and recommendations are included to improve this to in excess of 90 percent.     

Calibration of Precision Gimbaled Pointing Systems

Corrections of pointing data provided by gimbal readout transducers can be used to compensate for the errors that arise because of gimbal misalignments and inaccuracies in transducer readout. This paper reviews the sources of pointing error in precision gimbaled pointing systems and describes the techniques for determining them. In particular, a method of calibration that is suitable for systems in which constraints on gimbal travel preclude the use of conventional calibration procedures is presented, and the pointing readout accuracy that can be achieved by this method is evaluated.     

Angular Accuracy of a Scanning Radar Employing a Two-Pole Filter

A two-pole filter is proposed as a detector for a scanning radar. The optimum values of the filter coefficients are found and are approximated by a simple expression. The optimum two-pole filter requires a 0.15-dB increase in signal-to-noise ratio in order to provide the same detection capability as the optimum detector, and yields azimuth estimates whose standard deviation are within 15 percent of the Cramér-Rao lower bound. The estimator is simple to implement, avoiding the storage requirements of the moving window detector and the bias complications of the feedback integrator.     

On Optimal Control of Linear Systems in the Presence of Multiplicative Noise

This correspondence considers the problem of optimal regulator design for discrete time linear systems subjected to white state-dependent and control-dependent noise in addition to additive white noise in the input and the observations. A pseudo-deterministic problem is first defined in which multiplicative and additive input disturbances are present, but noise-free measurements of the complete state vector are available. This problem is solved via discrete dynamic programing. Next is formulated the problem in which the number of measurements is less than that of the state variables and the measurements are contaminated with state-dependent noise. The inseparability of control and estimation is brought into focus, and an "enforced separation" solution is obtained via heuristic reasoning in which the control gains are shown to be the same as those in the pseudo-deterministic problem. An optimal linear state estimator is given in order to implement the controller.