# Clutter-Masked Waveform Design for LPI/LPD Radarcom Signal Encoding
###### Abstract  
In this work we propose a method of in situ clutter deconvolution and modeling using experimentally obtained UWB radar data. The obtained clutter models are then used for random sequence encoding of radar-communication (radarcom) signals to achieve clutter-masked transmissions and improve communication security. We present the results of clutter modeling from the laboratory data obtained with the software-defined radar system. We then show that such clutter-masked radaracom signals generated using the local clutter model are highly likely to be interpreted as just clutter returns by an unauthorized interceptor. We also present the results of communication and radar performance of these radaracom signals and contrast them with those obtained using a linear frequency modulated waveform. It is shown that the proposed radarcom design method has high potential to achieve secure communications in adversarial conditions, while simultaneously addressing radar sensing needs. clutter modeling; radar-communication fusion; software-defined radar; UWB radar acomar  
this reason, clutter suppression/removal techniques have been studied, e.g., space-time adaptive processing (STAP) [6]. To better understand the impact of clutter and thus be more efficient in its removal, clutter modeling has been investigated, e.g., in [7] the authors used deconvolution to remove sea clutter from the radar returns based on the theoretical model of the former. In [8], cumulative disturbance was modeled as combination of clutter and noise. In [9; 10], methods to model clutter as spherically invariant random vectors (SIRV) were introduced. In none of those works, however, were any attempts to separate noise from the clutter model made. This may not be a requirement for subsequent clutter removal algorithms, still other uses for clutter modeling may necessitate such a delineation. There have been a variety of waveforms suitable for sensing, and communications studied recently as radarcom schemes have gained attention. In [11], noise-like radarcom signals were introduced using the Lorenz chaos system, with a flattened spectrum. This resulted in peak sidelobes (PSL) of \(-32\) dB over a bandwidth of 500 MHz. The signal included 300 communication symbols and a symbol length of 100. The Lorenz chaos approach was also used in [12] to create controlled chaos-based frequency modulated (CCBFM) waveforms PSL at \(-17\) dB. The bit error rate (BER) was measured to be 0.125 at an energy-per-bit to noise spectral density ratio (E\({}_{\text{b}}\)/N) between \(-5\) dB and \(2\) dB, and the BER was 0.001 at a (E\({}_{\text{b}}\)/N) of 10 dB. While the chaos-based waveforms are claimed to have good LPI/LPD properties, there were no quantifiable results presented in that regard yet. Also, since such signals are not part of the natural RF environment and may go above the noise floor, it may be easier for an interceptor to identify this part of the spectrum as potentially containing information. In contrast, our proposed method aims to create transmissions that represent the in situ clutter, leading to much higher likelihood that an interceptor will classify such intercepts as clutter returns and not communication data. Further differences between these approaches and our proposed method are that the Lorenz scheme in [11] uses well known modulation such as differential chaos shift keying (DCSK), which makes it more likely to be deciphered; additionally, the bits per seconds (bps) figure in [12] was significantly lower than what orthogonal frequency division multiplexing (OFDM) can provide. In [13], phase modulated continuous wave (PMCW) and OFDM access (OFDMA) were tested. OFDMA differs from OFDM in allocating users in both time and frequency instead of just time. Both methods had PSL of \(-9\) dB and sidelobe floors of \(-10\) dB. In [14], a survey was conducted of various joint radar and communication schemes; one notable version combined the linear frequency modulated (LFM) chirp and OFDM.