Millimetre Wave RADAR Spectra Simulation and Interpretation for Outdoor SLAM Ebi Jose, Martin D. Adams School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang Avenue 639798, Singapore. Email : ebi@pmail.ntu.edu.sg, eadams@ntu.edu.sg Abstract—Millimetre Wave RADARs are more robust than most other sensors used in outdoor autonomous navigation in that their performance is less affected by dust, fog, moderate rain or snow and ambient lighting conditions. This paper describes a method to accurately simulate the range spectra using the RADAR range equation. This is very important in robot navigation (eg. SLAM) for generating pre- dictions of what can be observed from different sensor locations and correspondingly, providing an interpretation for observed targets. To understand the MMW RADAR range spectrum and to simulate it accurately, it is necessary to know the noise distributions in the RADAR spectrum. A detailed noise analysis during signal absence and presence is carried out which shows various sources of noise affecting MMW RADARs. RADAR range bins are then simulated using the RADAR range equation and the noise statistics and are compared with real results in controlled environments. It will be demonstrated that it is possible to provide realistic predicted RADAR power/range spectra, for multiple targets down range. Feature detection from the RADAR spectra based on target presence probability is then explained. The detection technique uses binary hypothesis testing. Results are shown comparing a new probability based feature detection with other standard feature extraction techniques such as constant threshold on raw RADAR data and Constant False Alarm Rate (CFAR) techniques. The results show that the proposed algorithm is more robust compared to other detection techniques as it does not require human assistance. This work is a step towards robust outdoor SLAM with MMW RADAR based continuous power spectra. Index Terms - MMW RADAR, noise statistics, range estima- tion, Constant False Alarm Rate, target presence probability. I. I NTRODUCTION Current research on Simultaneous Localisation and Map- ping (SLAM) focuses on mining, planetary-explorations, fire emergencies, battlefield operations as well as on agricultural areas. MMW RADAR provides consistent and fairly accurate range measurements for the environmental imaging required to perform SLAM in dusty, foggy and poorly illuminated environments [1]. Millimetre wave RADAR signals have the ability to penetrate many objects and can provide information of distributed targets that appear in a single observation. This work is conducted with a 77 GHz Frequency Modulated Continuous Wave (FMCW) RADAR which operates in the millimetre wave region of the Electro-Magnetic Spectrum. For Localisation and Map building, it is necessary to predict the target locations accurately given a prediction of the vehi- cle/RADAR location. A method for accurately predicting the power-range spectra (or range bins) using the RADAR range equation and the knowledge of the noise distributions in the RADAR is explained in this paper. Predicted observations are formed using this predicted state and the given RADAR equation, system and noise analyses to construct “predicted range-bins”. The actual observations take the form of received power/range readings from the RADAR. Section II briefly summarises related work, while section III describes FMCW RADAR operation and the noise affecting the range spectra. Section IV describes how power-range spec- tra can be simulated (predicted observations). This utilises the RADAR range equation and a noise analysis which considers the propagation of noise from its source in the receiver through the RADAR electronics to the final range output. Methods for estimating the true range from power-range spectra are given in section IV where a new robust range estimation technique based on target presence probability is presented. Section VI shows that the proposed algorithm is more robust compared to other detection techniques such as constant threshold on the power spectra and Constant False Alarm Rate (CFAR) methods as it does not require human assistance. II. RELATED WORK In recent years RADAR for automotive purposes has gained interest in shorter range (< 200) metres applications. Most of the work in short range RADAR has focused on millimetre waves as this allows narrow beam shaping, which is necessary for higher angular resolution. Steve Clark [2] presented a method for fusing RADAR readings from different vehicle locations into a two dimen- sional representation. The method selects one range point per RADAR observation at a particular bearing angle based on a certain received signal power threshold level. This method takes only one range reading per bin which is the nearest power return to exceed that threshold to the RADAR, discard- ing all others. In [3] Clark shows a millimetre wave RADAR based navigation system which utilises artificial beacons for localisation and an extended Kalman filter for fusing multiple observations. Human intervention is required for adjusting the threshold as the returned signal power depends on various object’s RADAR Cross Section (RCS). Boehmke et al. [4] succeed in producing three-dimensional terrain maps using a pulsed RADAR with a narrow beam