Hi, I'm working on an application for TOA and TDOA for a set of sensor data. After matched filtering, I'm running my data through a 39-tap Hilbert Transform to ultimately obtain the signals' envelope and store the in-phase and quadrature components of the peaks for subsequent processing. Due to the filter latency, very close sources are not detectable. So I thought of using circular buffers whose lengths are equal to the Hilbert FIR filter and stitch these to my real data set; effectively, providing what I think is a reasonable workaround for the latency problem. I was wondering whether this approach makes sense to the DSP veterans here and whether there exist out there a neater solution. Would appreciate your input on this. Many thanks, -Manny
Filter latency and TDOA
Started by ●July 21, 2008
Reply by ●July 22, 20082008-07-22
On 22 Jul, 00:35, Manny <mlou...@hotmail.com> wrote:> Hi, > > I'm working on an application for TOA and TDOA for a set of sensor > data. After matched filtering, I'm running my data through a 39-tap > Hilbert Transform to ultimately obtain the signals' envelope and store > the in-phase and quadrature components of the peaks for subsequent > processing. > > Due to the filter latency, very close sources are not detectable. So I > thought of using circular buffers whose lengths are equal to the > Hilbert FIR filter and stitch these to my real data set; effectively, > providing what I think is a reasonable workaround for the latency > problem. > > I was wondering whether this approach makes sense to the DSP veterans > here and whether there exist out there a neater solution.The resolution problems have nothing to do with filter latency, regardless of whether the sources are close in angular domain or time domain. Whatever resolution issues you struggle with, first have a look at the time-bandwidth product and the Heissenberg inequality. These are fundamental properties which link resolution to the framelengths (or array lengths) of data under analysis. Rune