Frequency tracking with huge noise
might look at:


B. F. La Scala and R. R. Bitmead, "Design of an extended Kalman filter > frequency tracker," Acoustics, Speech, and Signal
Processing, 1994.



  Abstract: This paper discusses the problem of designing a frequency tracker using the extended Kalman filter (EKF). The design
  trade-off between balancing noise rejection and tracking at a maximal
  slew rate is considered, as are the effect of varying design noise
  covariance values. The performance penalties for over- and
  under-design of noise covariances are examined and theoretically
  supported design guidelines are suggested.


There's also the book :


Quinn, Barry G., and Edward James Hannan. The estimation and tracking of frequency. Vol. 9. Cambridge University Press, 2001.


As Peter noted, in SONAR, tracking low SNR tones is done but they typically run off a DFT.  If you want to go this route, you would have to do some experimentation on bin widths and short term averaging.  Fundamentally, you need to filter the signal down to a band that results in a positive SNR.  The band can contain more than a few bins, but the signal has to display a reliable peak when it occupies the bin.  A much more expensive approach would be a bank of chirps.  

I would also suggest, for your remark about process and measure noise being correlated.  One of the reasons I like the book is that they derive the KF directly from the case where measurement and process noise is correlated.


Kailath, Thomas, Ali H. Sayed, and Babak Hassibi. Linear estimation. Vol. 1. Upper Saddle River, NJ: Prentice Hall, 2000.