# Towards mmWave Altimetry for UAS: Exploring the Potential of 77 GHz Automotive Radars
## 7 Discussion  
The goal of this effort was to establish the applicability of mmWave automotive radars for radar altimeters of UASs. To realize this goal, the article has offered a discussion on the feasibility, benefits, and methodology for exploring the 77 GHz mmWave automotive radars in the wake of 5G interference in the dedicated 4.2-4.4 GHz band. The cost-effectiveness, easy accessibility, and FMCW waveform offered on the MMIC position them as a lucrative candidate. In this work, their suitability with intrinsic hardware limitations was appraised theoretically. With very few reference works for researchers and academicians to benefit from, a tutorial-themed discourse comprising a simplified mathematical expression was furnished. Another important milestone of this work was to present a brief and meaningful discussion on backscattering from the ground surface in a mmWave radar altimeter scenario. The scope of this discussion for 77 GHz automotive radars being evaluated for a radar altimeter use case was previously unreported. This direction is poised to aid youthful researchers and system engineers alike in better understanding the performance metrics. The authors' comments throughout the entire course of the text have been aimed at providing the basis for the optimization of available resources. Nevertheless, it is in no way implied that the hardware limitations cannot be improved upon. For instance, \(R_{max}(IF_{max},S)\) was found to be a bottleneck that brought the \(Alt_{max}\) down. The benefits of migration to the 77 GHz band remain equally applicable if the problem of the mmWave radar altimeter design is approached with a modular radar that offers the flexibility to increase \(IF_{max}\). Despite a complex baseband architecture, this direction demands a higher \(F_{s}\). Subsequently, a proportionate increase in \(N_{FFT}\) is poised to keep \(\Delta R(F_{s},N_{FFT},S)\) relatively constant while offering an increase in \(R_{max}(IF_{max},S)\) proportional to \(IF_{max}\). However, it must be noted that having a higher \(N_{FFT}\) requires more processing resources, which is possible with a dedicated, more powerful processor. It was underscored in Section 3 that EM waves traversing at 77 GHz are expected to experience a high FSPL followed by a compromised SNR at the receiver. Contrariwise, it was observed that a higher NRCS for smaller wavelengths compensates for the high FSPL. This, along with a wide HPBW in both planes and a longer observation window, enables a promising \(R_{max}(SNR_{min})\). In summary, impartial to the choice of hardware, the discussions and findings of this article are composed to propel the narrative towards the mmWave altimeter. Nevertheless, a modular approach is certain to add volume and cost overhead. The lack of dedicated MOPSs for radar altimeters of UASs required some deliberation for repurposing commercial application standards for the required use case. The authors' notes are backed by the theoretical and mathematical rationale to rationalize the operational requirements accordingly. The discussion on the performance metrics and their interconnected nature required a careful approach in order to exploit the performance to its fullest. The authors exercised great care in presenting a systems engineering approach. To culminate the work, an example test case was presented with operational requirements followed by the derived radar specifications. It is appropriate to point out that this body of work is the first in a series of an ongoing project concerning mmWave radar altimeters. The scope of future work is stated in Section 6. For the sake of completeness, it is stated that the sequential approach towards the eventual goal shall encompass a dedicated text on signal processing. A completely novel direction is the exploitation of ML/DL methods to classify the flight modes in UAV operation for subsequent waveform optimization.