Data Compression via Pulse-to-Pulse Redundancy for Radar Emitter Location

An effective method for geolocation of a radar emitter is to intercept its signal at multiple platforms and share the data to allow measurement of the time-difference-of-arrival (TDOA) and the frequency-difference-of-arrival (FDOA). This requires effective data compression. For radar location we show that it is possible to exploit pulse-to-pulse redundancy. A compression method is developed that exploits the singular value decomposition (SVD) to compress the intercepted radar pulse train. This method consists of five steps: (i) pulse gating, (ii) pulse alignment, (iii) matrix formation, (iv) SVDbased rank reduction, and (v) encoding. Matrix formation places aligned pulses into rows to form a matrix that has rank close to one and SVD truncation gives a low rank approximate matrix. We show that (i) compression is maximized if the matrix is made to have two-thirds as many rows as columns and (ii) truncation to a rank-one matrix is feasible. We interpret this as extracting a prototype “pulse trainlet.” The maximum compression ratio is expressed in terms of the number of pulses and the number of samples per pulse and point out a particularly interesting and important characteristic – the compression ratio increases as the total number of signal samples increases. Theoretical and simulation results show that this approach provides a compression ratio up to about 30:1 in practical signal scenarios.