Sun-Mog Hong

Optimal scheduling of track updates in phased array radars

The optimal scheduling of track updates in phased-array radars is considered to minimize the radar energy resources required for track maintenance. The energy-optimal scheduling problem is formulated into a nonlinear optimal control problem, and a numerical procedure for its solution is presented. The scheduling problem is solved for typical examples to illustrate a pair of optimal sequences of track update intervals and signal-to-noise ratios (SNRs).

Optimization of waveform and detection threshold for range and range-rate tracking in clutter

We address an optimization problem to obtain the combined sequence of waveform parameters (pulse amplitudes and lengths, and FM sweep rates) and detection thresholds for optimal range and range-rate tracking in clutter. The optimal combined sequence minimizes a tracking performance index under a set of parameter constraints. The performance index includes the probability of track loss and a function of estimation error covariances. The track loss probability and the error covariances are predicted using a hybrid conditional average algorithm. The effect of the false alarms and clutter interference is taken into account in the prediction. A measurement model in explicit form is also presented which is developed based on the resolution cell in the delay-Doppler plane for a single Gaussian pulse. Numerical experiments were performed to solve the optimization problem for several examples.

Modeling and parameter optimization of agile beam radar tracking

In the work presented here, we address parameter optimization for agile beam radar tracking to minimize the radar resources that are required to maintain a target under track. The parameters to be optimized include the track-revisit interval as well as the sequence of pairs of target signal strengths and detection thresholds associated with successive illumination attempts in each track-revisit. The effects of false alarms and clutter interference are taken into account in the modeling of target detection and in the characterization of tracking performance. Based on the detection model and tracker characterization, the parameter optimization problem is formulated. Typical examples of the optimization problem are numerically solved. The optimal solution gives an off-line scheduling of the parameter set. It also provides insight into the selection of a near-optimal parameter set that is appropriate for real-time implementation.

Physiological Tremor Estimation With Autoregressive (AR) Model and Kalman Filter for Robotics Applications

This paper focuses on developing a simple and efficient tremor estimation algorithm suitable for real-time applications. Autoregressive model in combination with Kalman filter is employed for tremor estimation in robotics devices. A research is conducted with tremor data recorded from surgeons and novice subjects for model identification and characteristics. Results show that appropriate choice of model parameters improves the estimation accuracy. Comparison with existing tremor estimation methods is performed to analyze the performance. Experimental results for 1-DOF tremor estimation are provided to validate the approach.

Multiple-target tracking and track management for an FMCW radar network

A multiple-target tracking problem for a frequency-modulated continuous-wave (FMCW) radar network is formulated and an integrated track management system is presented to solve the tracking problem in the presence of clutter. The FMCW radar network obtains beat frequency measurements with multiple collocated radars, each transmitting a sequence of chirps. The beat frequency measurements are associated to tracks directly in the beat frequency measurement space. The direct association eliminates range/range-rate calculations and multilateration processing, and it allows to process beat frequency measurements sequentially on a chirp by chirp basis. The sequential processing effectively decomposes the measurement-to-track association problem into a series of two-dimensional assignment problems that can be solved with much less computational effort. The solution to the measurement-to-track association problem is utilized to initiate and form new tracks and to update or delete existing tracks. Monte Carlo simulations were performed to evaluate the performance of the track management system.

An analytic approximation of information reduction factor for performance prediction of PDA tracking

An analytic approximation of the information reduction factor is presented in an efficient manner for the case of two-dimensional measurement vector and a four sigma validation gate. This analytic approximation allows us to evaluate efficiently performance prediction for the probabilistic data association (PDA) filter using the hybrid conditional average (HYCA) algorithm.

Approximations for Detection Probability and Measurement Accuracy Taking into Account Antenna Beam-Pointing Losses

Expressions are presented for the probability of target detection and the measurement accuracy of the detection, taking into account the effects of antenna beam-pointing error. Evaluation of these expressions requires numerical integration, which is computationally expensive. Approximate but analytic and efficient expressions are also presented. Numerical examples are given to present the relative accuracy of our analytic approximations.

Optimization of waveform and detection threshold for target tracking in clutter

We formulate an optimization problem to obtain the combined sequence of waveform parameters (pulse amplitudes and lengths, and FM sweep rates) and detection thresholds for optimal target tracking in clutter. The optimal combined sequence minimizes a tracking performance index under a set of parameter constraints. The performance index can include the probability of track loss and the estimation accuracy. The effect of the false alarms and clutter interferences is taken into account in quantifying the performance index. A measurement model is developed based on the resolution cell in the delay-Doppler plane for a Gaussian pulse. Numerical experiments were performed to solve the optimization problem for several example problems.

Control of waveforms and detection thresholds for optimal target tracking in clutter

An optimization problem is formulated to obtain the combined sequence of waveform parameters (pulse amplitudes and lengths, and FM sweep rates) and detection thresholds for optimal target tracking in clutter. The optimal combined sequence minimizes a tracking performance index that is a function of the probability of track loss and the estimation accuracy. A measurement model is also developed based on the resolution cell in the delay-Doppler plane for a Gaussian pulse.

Estimation of radar cross section of a target under track

In allocating radar beam for tracking a target, it is attempted to maintain the signal-to-noise ratio (SNR) of signal returning from the illuminated target close to an optimum value for efficient track updates. An estimate of the average radar cross section (RCS) of the target is required in order to adjust transmitted power based on the estimate such that a desired SNR can be realized. In this paper, a maximum-likelihood (ML) approach is presented for estimating the average RCS, and a numerical solution to the approach is proposed based on a generalized expectation maximization (GEM) algorithm. Estimation accuracy of the approach is compared to that of a previously reported procedure.