# Towards mmWave Altimetry for UAS: Exploring the Potential of 77 GHz Automotive Radars
## 6 Future Work and Challenges
### Future Work  
This article is the initial segment of an ongoing mmWave radar altimeter project. This text concentrates on a careful literature review, an exploration of MOPSs, an examination of the state of the art, and the establishment of the theoretical foundation. Next in line is to identify relevant signal-processing techniques for true altitude estimation. In the presence of multiple scatterers in the antenna beamwidth, the most useful altitude estimate is the one obtained directly beneath the nose of the UAS platform. To cater to this requirement, one such direction is the exploration of mmWave TDM-MIMO [32] for the radar altimeter use case. Having a spatial resolution in radar altimeters is a nascent concept that can be extremely useful in true altitude estimation. Moreover, to make the best use of processing resources on automotive radars, it is imperative that we study and evaluate the signal-processing techniques prevalent in ADASs for their applicability in radar altimeters. For instance, the efficacy of the CFAR algorithm for the detection of the ground and the selection of associated design parameters for this particular application is unreported. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Value** & **Remarks** \\ \hline \(\Delta t_{max}\) & 26 ms & Max time b/w data updates (42) \\ \(U_{min}\) & 38 Hz & Minimum update rate (43) \\ \(T_{c}\) & 1 ms & Chirp duration \\ \(S\) & 1.91 MHz/us & Chirp slope \\ \(B\) & 1.91 GHz & Chirp BW (3) \\ \(\Delta R(B)\) & 0.07 m & Function of chirp BW (20) \\ \(\Delta R(F_{s},N_{FFT},S)\) & 0.85 m & Function of sampling, FFT and slope (44) \\ \(N_{FFT}\) & 1024 & FFT size \\ \(Alt_{min}\) & 0.85 m & Minimum measurable altitude (47) \\ \(Alt_{acc}\) & 0.85 m & Altitude accuracy (25) \\ \(N\) & 16 & Number of chirps/frame \\ \(T_{F}\) & 16 ms & Frame duration (27) \\ \(B_{n}\) & 62.5 Hz & Noise BW (28) \\ \(P_{n}\) & \(-\)141.27 dBm & Noise power (29) \\ \(\sigma_{0}\) & 2.47 & Normalized RCS (23) \\ \(R_{max}(SNR_{min})\) & 4548.9 m & Function of minimum SNR (31) \\ \(R_{max}(I_{max},S)\) & 783.3 m & Function of IF, BW, and Slope (16) \\ \(R_{max}(N_{FFT},\Delta R)\) & 870.4 m & Function of FFT and resolution (49) \\ \(Alt_{max}\) & 783.3 m & Maximum measurable altitude (50) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Waveform and altimeter specifications. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Requirement** & **Value** & **Remarks** \\ \hline \(\theta_{a}\) & 56\({}^{\circ}\) & HPBW azimuth [62] \\ \(\theta_{c}\) & 28\({}^{\circ}\) & HPBW elevation [62] \\ \(P_{t}(\text{dBm})\) & 12.5 dBm & MAX Tx power, IWR1843 [62] \\ \(G_{t}\) & 10.5 dBi & IWR1843 Boost [62] \\ \(G_{r}\) & 10.5 dBi & IWR1843 Boost [62] \\ \(f\) & 77 GHz & Operating frequency [62] \\ \(\lambda\) & 3.9 mm & Wavelength \\ \(tan(0)\) & 0.14 & RMS surface slope \\ \(F\) & 15 dB & Receiver noise figure \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Hardware Specifications of Radar. Similarly, signal-processing algorithms used in industrial applications can be applied to improve range accuracy. Liquid-level sensing radar systems use algorithms like Zoom-FFT [67]. There is plenty of room for exploration and use in the very-high-accuracy landing requirements of UASs or commercial aviation. Zoom-FTT provides a coarse range estimation, followed by magnifying a specific portion of the frequency spectrum for accuracy enhancement beyond the conventional limits of the radar. Accuracies in the mm range have tremendous application avenues specifically as a backup for weight-on-wheel systems in fixed-wing UASs or commercial aircraft. There is a dire need to extend the scope of the work toward experimental verification across varied ground surfaces, including snow, water, grass, and concrete. More importantly, the performance of the radar altimeter against complex textures such as large forest and green vegetation may warrant careful signal-processing algorithms.