Research On Electromagnetic Scattering Characteristics Of Birds And Detection Of Echoes From Birds

Bird strike accidents are the top threats to global aviation safety.Researches focus on methods to reduce bird strike hazards by using radar systems.Yet,guided by limited fundamental conclusions in radar ornithology,current avian radar systems,and external multistage radar systems can only forecast general information about bird activities,but not alert bird strikes in real-time.Thereby,bird strike accidents continue to rise,causing enormous economic losses.Here,the author conducts systematized research on radar detection of birds,by building a new scattering model for birds,measuring radar echoes from flying birds in the microwave anechoic chamber,designing automatic target recognition methods to identify radar echoes from birds based on radar signatures and extracting bioinformation from radar data.Since the early researches in radar ornithology neither full understands electromagnetic scattering characteristics of a target nor adopts appropriate measuring methods,the established water sphere model of bird targets cannot correctly describe the scattering characteristics of birds.And then,the avian radar systems adopting the water sphere model theory cannot detect bird targets in real-time,and disparity exists between avian information abstracted from radar data and observed by human beings.Introducing scattering regions theory and kinematics analysis,the author provides the theory of time-varying wingbeat corner reflector effect to explain the modulation mechanism on bird radar echoes posed by wingbeats,in that during specific flapping gaits,the wings and body of birds in flight act as corner reflectors.Hence,most radar echoes fall upon either face impinge onto the other face,and subsequently reflected towards the illuminator,thus contributing 10 dB to bird radar cross-section.Furthermore,the author argued that when the radar band is in the optical region,bird target can be modeled by some geometric structures;as such,those radar signatures registered by those geometric structures can be extracted to be as scattering features for automatic target recognition of birds echoes.The author design a novel method to measure radar echoes from flying birds in the microwave anechoic chamber.The results confirm both the time-varying wingbeat corner reflector effect and the azimuth scattering model of bird targets.The author also discovers some scientific findings.The Wingbeat corner reflector effect can amplify bird signals within all measured bands,thus improve radar detection range of birds.Nevertheless,only in the optical region,radar target recognition based on shape difference is viable.Besides,both respiratory movement and wingbeat motion can cause shape change of a bird,and the latter one is responsible for the major fluctuation of bird echoes.The measured fluctuation value of 10 dB is consistent with the theoretical contribution of the wingbeat corner reflector model.Moreover,neither wingbeat or not,it seems bird shape affects bird signals more than bird size.It indicates that bird species can be identified from radar echoes due to difference in shapes.Avian radar systems must fulfill those requirements,including long-distance,full height,real-time,high detection,low missed targets,and low false alarm,to be able to detect bird targets in real-time.And the detection accuracy and time cost are the key.The author chooses radar bands in the optical region for detecting birds for two benefits.One is that the detection range of birds can be increased by using the wingbeat corner reflector effect to amplify the bird radar cross-section.The other one is that the scattering mechanism in the optical region can provide intelligence about bird shape for automatic target recognition.The provided method of integrated detection and identification and the technology of recognition while scanning can separate interference from ground objects,and classify radar echoes from birds and drones aloft.Thus,it reduces the false alarm and missed alarm at the same time,lower the training requirements for radar operators,improve the response speed of the system,and achieve the real-time warning of bird strikes for avian radar systems.The author also contributes some findings for radar ornithology.The position of birds’ feet in flight can be utilized to classify bird size.The author finds that large birds habitually carry their feet stretched out behind them during flight,leaving their feet apart from the body and visible to both human observation and radar detection,while small birds tend to carry their feet drawn up in front,clinging to the body,thus hiding their feet from detection.Radar signatures registered by the wingbeat corner reflector effect can work as a chronophotograph in radar data to record bird flight modes.When a bird is flapping its wings,the corner works at a right angle,and the wingbeat corner reflector strongly modulates the radar signal;therefore,the contribution is strong and stably approaches 10 dB.During gliding,the wingbeat corner reflector fades away,the modulation effect significantly decreases,and the contribution approaches 0dB.This difference can assist in classifying bird flight modes between flapping and gliding over a long sampling period.Besides,the model of estimating bird migration,population by using radar data may overestimate the bird population.They need true radar cross-section of a single bird by considering contributions from wing beats,as well as consider adjusting the rectification method by taking the place of radar data of mental spheres in different radar bands by using radar data of calibration kits owning similar composition as birds in the same radar band.