Joint Transmit and Receive Filter Optimization for Sub-Nyquist Delay-Doppler Estimation

In this article, a framework is presented for the joint optimization of the analog transmit and receive filter with respect to a parameter estimation problem. At the receiver, conventional signal processing systems restrict the two-sided bandwidth of the analog pre-filter $B$ to the rate of the analog-to-digital converter $f_s$ to comply with the well-known Nyquist-Shannon sampling theorem. In contrast, here we consider a transceiver that by design violates the common paradigm $B\leq f_s$. To this end, at the receiver, we allow for a higher pre-filter bandwidth $B>f_s$ and study the achievable parameter estimation accuracy under a fixed sampling rate when the transmit and receive filter are jointly optimized with respect to the Bayesian Cram\'{e}r-Rao lower bound. For the case of delay-Doppler estimation, we propose to approximate the required Fisher information matrix and solve the transceiver design problem by an alternating optimization algorithm. The presented approach allows us to explore the Pareto-optimal region spanned by transmit and receive filters which are favorable under a weighted mean squared error criterion. We also discuss the computational complexity of the obtained transceiver design by visualizing the resulting ambiguity function. Finally, we verify the performance of the optimized designs by Monte-Carlo simulations of a likelihood-based estimator.Comment: 15 pages, 16 figure

Orbiter-orbiter and orbiter-lander tracking using same-beam interferometry

Two spacecraft orbiting Mars will subtend a small angle as viewed from Earth. This angle will usually be smaller than the beam width of a single radio antenna. Thus the two spacecraft may be tracked simultaneously by a single Earth-based antenna. The same-beam interferometry (SBI) technique involves using two widely separated antennas, each observing the two spacecraft, to produce a measurement of the angular separation of the two spacecraft in the plane of the sky. The information content of SBI data is thus complementary to the line-of-sight information provided by conventional Doppler data. The inclusion of SBI data with the Doppler data in a joint orbit estimation procedure can desensitize the solution to gravity mismodeling and result in improved orbit determination accuracy. This article presents an overview of the SBI technique, a measurement error analysis, and an error covariance analysis of some examples of the application of SBI to orbit determination. For hypothetical scenarios involving the Mars Observer and the Russian Mars '94 spacecraft, orbit determination accuracy improvements of up to an order of magnitude are predicted, relative to the accuracy that can be obtained by using only Doppler data acquired separately from each spacecraft. Relative tracking between a Mars orbiter and a lander fixed on the surface of Mars is also studied. Results indicate that the lander location may be determined to a few meters, while the orbiter ephemeris may be determined with accuracy similar to the orbiter-orbiter case

Multipath Parameter Estimation from OFDM Signals in Mobile Channels

We study multipath parameter estimation from orthogonal frequency division multiplex signals transmitted over doubly dispersive mobile radio channels. We are interested in cases where the transmission is long enough to suffer time selectivity, but short enough such that the time variation can be accurately modeled as depending only on per-tap linear phase variations due to Doppler effects. We therefore concentrate on the estimation of the complex gain, delay and Doppler offset of each tap of the multipath channel impulse response. We show that the frequency domain channel coefficients for an entire packet can be expressed as the superimposition of two-dimensional complex sinusoids. The maximum likelihood estimate requires solution of a multidimensional non-linear least squares problem, which is computationally infeasible in practice. We therefore propose a low complexity suboptimal solution based on iterative successive and parallel cancellation. First, initial delay/Doppler estimates are obtained via successive cancellation. These estimates are then refined using an iterative parallel cancellation procedure. We demonstrate via Monte Carlo simulations that the root mean squared error statistics of our estimator are very close to the Cramer-Rao lower bound of a single two-dimensional sinusoid in Gaussian noise.Comment: Submitted to IEEE Transactions on Wireless Communications (26 pages, 9 figures and 3 tables