Nonlinear suppression of range ambiguity in pulse Doppler radar

Coherent pulse train processing is most commonly used in airborne pulse Doppler radar, achieving adequate transmitter/receiver isolation and excellent resolution properties while inherently inducing ambiguities in both Doppler and range. As first introduced by Palermo in 1962 using two conjugate LFM pulses, the primary nonlinear suppression (NLS) objective involves reducing range ambiguity, given the waveform is nominally unambiguous in Doppler, by using interpulse and intrapulse coding (pulse compression) to discriminate the received ambiguous pulse responses. By introducing a nonlinear operation on compressed (undesired) pulse responses within individual channels, ambiguous energy levels are reduced in channel outputs. The proliferation of high-speed digital signal processing capability and discrete code development occurring since 1962, greatly improves the feasibility of implementing NLS using code sets of multiple codes. This research expands the NLS concept using discrete coding and processing. A general theory is developed showing how NLS accomplishes ambiguity surface volume removal without requiring orthogonal coding. Useful NLS code sets are generated using combinatorial, simulated annealing optimization techniques—a general algorithm is developed to extended family size, code length, and number of phases (polyphase coding). An adaptive reserved code thresholding scheme is introduced to efficiently and effectively track the matched filter response of a target field over a wide dynamic range, such as normally experienced in airborne radar systems. An evaluation model for characterizing NLS clutter suppression performance is developed—NLS performance is characterized using measured clutter data with analysis indicating the proposed technique performs relatively well even when large clutter cells exist.