Micro-Doppler Signature Extraction with Multibeam Radar

Multibeam radars (MBRs) enable multiple independent channels by simultaneously exploiting spatial and waveform diversity. Orthogonal waveforms are employed to form multiple independent antenna beams, each one providing a different function and using different dedicated radar resources. This paper investigates sidelobe levels in MBRs and presents a comparison with those of an Electronic Steerable Array (ESA) that employs a single waveform in transmission to generate multiple simultaneous beams. Simulations are carried out for a 3-channel MBR transmitting quasi-orthogonal Linear Frequency Modulated (LFM) waveforms at Ku band. The response of the MBR to an ideal point target as a function of aspect angle as well as that to multiple targets in different locations has been investigated. Results corroborate the analytical findings and show that the sidelobe levels with respect to angle, at the target range, are attenuated by the cross-ambiguity function properties between the waveforms employed. The range response to a target in low channel isolation suffers from cross-channel interference that may alter the noise floor characteristics of the radar, hence stressing the importance of suitable waveform selection.

This letter reports the measurements and results of tests conducted on the detection of unmanned aircraft systems (UASs) or drones using a millimeter-wave (mmWave) automotive radar sensor. Designed for the detection of automotive targets with radar cross section (RCS) in excess of 20 dBsm, these miniaturized radar sensors have demonstrated detection and ranging performance in detecting a UAS, whose RCS is typically less than -15 dBsm. The sensor operates in the 76-81 GHz (mmWave) band and employs the frequency-modulated continuous-wave principle with a maximum output power of 16 mW. The detection capability of the sensor in terms of range and radial velocity measurements was investigated using a Type-I micro-UAS with a mean RCS less than -20 dBsm. In addition to detection, ranging, and velocity measurements, the RCS and the micro-Doppler signature measurements of the UAS in flight are also presented. The measurements and analysis suggest that these mmWave sensors are ideally suited as low-cost sensors for the detection of micro- and mini-classes of UASs at short ranges. The micro-Doppler signature analysis reveals the versatility of mmWave sensors in the extraction of micro-Doppler signatures, which serves as an effective tool for the classification of UASs from other airborne nuisance targets such as birds and moving clutter. © 2017 IEEE.

This chapter addressed the challenges and opportunities that come along with the introduction of micro -Doppler signatures in automotive radar applications. Here, a major interest lies in the development of methods to protect vulnerable road users, i.e. pedestrians, cyclists, etc. As has been shown in various studies, micro -Doppler signatures enable a way to identify these targets, thereby making active protection measures possible. Apart from the well -studied single -target scenario, this chapter focused on the far more realistic multi -target scenario and presented an experimentally validated method for simultaneous micro -Doppler signature extraction and classification using a 94 GHz FMCW radar. Central to any multi -target classification system is a tracking algorithm as it links signatures with dynamic targets. Furthermore, it has been shown that by solely using micro -Doppler information, the motion of a pedestrian (Section 12.3.3.1, Case 2) can be determined and separated from other vulnerable road users (Section 12.3.3.1, Case 1). Future work might include the fusion of tracking and micro Doppler signature information to increase the overall classification performance. In the scope of this chapter, it was not feasible to cover every approach in equal depth. The presented approach is adequate but by no means the only one. Therefore, throughout the chapter other solutions are mentioned and referenced.

The micro-Doppler signature of a target can provide more information for target classification and recognition. Battlefield surveillance radar has low Doppler resolution, which provide coarse micro-Doppler signature. In order to get more detailed micro-Doppler signature, high-resolution time-frequency distribution is necessary. In this paper, we use S-Wigner distribution(SWD), compared with STFT, to analysis the micro-Doppler signature of vibratory and three typical ground targets in battlefield.

Mechanical vibration or rotation of a target or structures on the target may induce additional frequency modulations on the returned radar signal which generate sidebands about the target's Doppler frequency, called the micro-Doppler effect. Micro-Doppler signatures enable some properties of the target to be determined. In the paper, the micro-Doppler effect in radar is introduced and the mathematics of micro-Doppler signatures is developed. Computer simulations are conducted and micro-Doppler features in the joint time - frequency domain are exploited.

Ultra-wideband radar-based penetrating detection and recognition of human activities has become a focus on remote sensing in various military applications in recent years, such as urban warfare, hostage rescue, and earthquake post-disaster rescue. However, an excellent micro-Doppler signature (MDS) extracting method of human motion with high time-frequency resolution, outstanding anti-interference ability, and extensive adaptability, which aims to provide favorable and more detailed features for human activity recognition and classification, especially in the non-free space detection environment, is in great urgency. To cope with the issue, a multiple Hilbert-Huang transform (MHHT) method is proposed for high-resolution time-frequency analysis of finer-grained human activity MDS hidden in ultra-wideband (UWB) radar echoes during the through-wall detection environment. Based on the improved HHT with effective intrinsic mode function (IMF) selection according to the cosine similarity (CS) principle, the improved HHT is applied to each channel signal in the effective channel scope of the UWB radar signal and then integrated along the range direction. The activities of swinging one or two arms while standing at a spot 3 m from a wall were used to validate the abilities of the proposed method for extracting and separating the MDS of different moving body structures with a high time-frequency resolution. Simultaneously, the corresponding relationship between the frequency components in MHHT-based spectra and structures of the moving human body was demonstrated according to the radar Doppler principle combined with the principle of human body kinematics. Moreover, six common finer-grained human activities and a piaffe at different ranges under the through-wall detection environment were exploited to confirm the adaptability of the novel method for different activities and pre-eminent anti-interference ability under a low signal-noise-clutter ratio (SNCR) environment, which is critical for remote sensing in various military application, such as urban warfare, hostage rescue, earthquake post-disaster rescue.

The groundbreaking advancement of micro unmanned aerial vehicles (micro-UAVs) has been staggering. The diversity of micro-UAV operations is demanding in most sectors. However, the current regulatory framework for the civilian use of these devices is still insufficient. The operation of micro-UAVs may pose risks, including privacy violations and collision hazards. To address these concerns, a radar with advanced processing is needed. This study presents a preliminary design of an S-band continuous wave (CW) radar, which was simulated using MATLAB. The size of the rotating propeller blades of the micro-UAV ranges from 20 to 40 cm in length, while the size of a bird’s flapping wing measures 35 cm in length, comprising 22 cm for the upper arm and 13 cm for the lower arm. The analysis was conducted under hovering conditions, where the target's main body is stationary while its micro-parts move continuously. The Short-Time Fourier Transform (STFT) analysis successfully identified the unique signature of both targets. The results showed that the S-band CW radar design at 5 GHz is effective in extracting the micro-Doppler signature of a bird versus a micro-UAV. The extracted features can be used as additional characteristics for target classification in the future.

Waveform diversity has been investigated by various organizations for a number of specific multiple function systems for about ten years. Applications that are being investigated include: • Multi-Mission Systems, including joint radar/embedded communications and simultaneous multi-mission radar • Advanced Target Classification, using multi-static imaging or multi-band/multi-static operation • Multi-Static Surveillance, including using distributed apertures to provide improved detection, tracking and interference rejection • Radars with unique modulation or unique spectrum usage. Each of these applications has constraints that prevent them from being accomplished with conventional waveforms. However, the greater design space of waveform diversity may provide the required capability. In previous work, multi-mission waveform methodology was extended to provide interleaved waveforms sequentially radiated from an aperture, and simultaneous orthogonal waveforms radiated from sub-apertures of the radar system. But effective operation in other modes (track, id, handoff) will require greater flexibility than is available with only the interleaved and sub-aperture approaches. A further advance in multi-mission waveform is required. Orthogonal waveforms must be radiated from the whole aperture simultaneously in addition to the mode using sub-apertures. In fact, a full capability multi-mission radar would require all three modes and the goal of our ongoing effort is to develop and demonstrate such a capability. When this goal is met, airborne radar systems concepts can be developed to meet a full spectrum of multi-mission needs. Our effort to develop simultaneous waveforms for air and ground surveillance (SWAGS) focuses on the critical software and hardware technologies required to make this full capability multi-mission radar feasible.

Multiple-input multiple-output radar waveform diversity design has received much attention, but many of existing waveforms are lack of a large time-bandwidth product. This paper proposes an orthogonal frequency division multiplexing (OFDM) chirp waveform diversity design scheme to generate four waveforms with good correlation properties, ambiguity performance and Doppler tolerance. The method jointly utilizes classic chirp waveform and OFDM to conduct multi-carrier modulation. This scheme enables us to exploit full bandwidth for each waveform and thus has an high frequency utilization efficiency. The modulation and demodulation of the four OFDM chirp waveforms are presented. The performance of the designed waveforms is analyzed by the correlation and ambiguity functions. Simulation results validate that our proposal can generate more orthogonal waveforms without significant performance degradation.

Ground moving target indication (GMTI) plays an important role in surveillance and reconnaissance applications, but it is a difficult problem due to the impacts of stationary clutter. This paper proposes a multichannel synthetic aperture radar (SAR) using waveform diversity, namely, multiple-input multiple-output (MIMO) SAR and distinct carrier frequency for GMTI applications. The proposed approach employs MIMO configuration with multiple antennas in azimuth and orthogonal waveform diversity. In doing so, multiple independent transmit-receive channels are formulated at the receiver. Since each antenna uses both waveform diversity and distinct carrier frequency, after clutter cancellation and noise suppression by the displaced phase center antenna (DPCA) and along-track interferometry (ATI) combined processing algorithm, the cross-track velocity is estimated through double-interferometry processing. Next, the Doppler parameters of moving targets are estimated with the fractional Fourier transform algorithm and then GMTI is obtained by a joint signal processing algorithm. Finally, the moving targets are focused with a general chirp scaling imaging algorithm. All the proposed methods are verified by simulation results.

The Short Time Fourier Transform (STFT) constructs the instantaneous spectrum of an observed dataset after applying a temporal taper for the sake of micro-Doppler feature extraction. Here, the temporal window applied to the STFT is adjusted proportionally to the instantaneous periodicity of the dataset as to establish more consistent UAV micro-Doppler signatures and improve the separability of relevant features. The outlined approach is developed in the context of UAV rotor blade analysis. Techniques for estimating the periodicity of the radar returns and examining the temporal correlation of the signal are presented. To demonstrate the efficacy of the proposed data-driven STFT algorithm, simulated and experimentally measured results of UAV rotor blades are analyzed.

The detection of radar micro Doppler signature which require high frequency and time resolution is of prime importance to the military sector given the destructive capabilities of them. Today’s state of art radar uses joint time frequency analysis (JTFA) based on short time Fourier transform (STFT) for micro Doppler signature analysis. In this paper, we implement JTFA using discrete wavelet packet transform (DWPT) for analysis of micro Doppler signature. The wavelet packet based approach is demonstrated for micro Doppler target with different rotation rate and different number of scatterers and found that it is a good alternative for JTFA analysis as compared to Fourier transform.KeywordsPulsed radarsMicro doppler targetJTFASpectrogramFourier transformSTFTWavelet transformDSPWavelet packet transform

Objective: Advancement in radar technology is moved from single antenna based system to multiple antenna system. From the viewpoint of the radar performance improvement, analysis of low Radar Cross Section (RCS) target detectability in rich scattering environment is utmost important. Methods: From the perspective of the advancement of the radar signal processing, phased array radar and MIMO radar have been already explored. This paper deals with the phased-MIMO radar, exploiting coherence signal processing gain and waveform diversity. Joint combination of coherency and diversity will improve the radar performance. Improvements: This paper deals with the analysis on the trade-off between the coherency and spatial diversity. The superiority of phased-MIMO radar, over other two systems, has been presented with respect to some selected parameters as in this paper.

Recent advances in Radar Remote Sensing cover an impressive list of developments, such as: waveform diversity, polarization diversity, frequency diversity, input-output channel diversity (MIMO), beam-forming and beam tailoring in send-and-receive modes!

A preliminary Doppler analysis on a man walking in free space at 1 GHz is presented in this paper. Firstly, the back-scattered response of the moving target has been provided by a simulation tool based on physical optics (PO) theory. Then, a short-time Fourier transform (STFT), a reassignment spectrogram (RE-Spect) and a Wigner-Ville distribution (WVD) have been employed to the data, in order to characterize the micro-Doppler signature of the walking human body. The results are based entirely on numerical tests. The investigation on the time variations of the Doppler spectrum of moving targets at lower frequencies is of interest for the emerging radar applications devoted to the detection and tracking of people in highly cluttered environment.