Detection, localization and tracking of aircraft sing acostic vector sensors Hans-Elias de Bree, Jelmer Wind, Pascal de Theije Microflown Avisa PO box 225, 682CE Arnhem, The Netherlands ABSTRACT Acostic aircraft tracking systems are a sefl addition to RADAR, becase they are a cost-effective method avoid RADAR gaps and they cannot be jammed. Frthermore, acostic systems work well at close range (a few kilometers at most) whereas RADAR systems are predominantly sed for long range applications. Traditionally, arrays of microphones are sed to determine the location of acostic sorces. Acostic vector sensors (AVS) consist of a single pressre microphone and three perpendiclar particle velocity sensors, all monted within a few millimeters. These sensors can measre the sorce direction from in a freqency band exceeding Hz to khz. In earlier research, it has been shown that these sensors make it possible to track the path of an aircraft sing the direction information and Doppler processing []. This article considers these earlier reslts, as well as new detection methods of propeller driven aircraft. A theoretical backgrond is given and experimental reslts are shown. Keywords: Acostic Vector Sensors, aircraft. INTRODUCTION This paper reports the ongoing R&D towards the detection, classification and localization of propeller driven aircraft. With acostic vector sensors (AVS s) it is possible to determine the direction of arrival (DOA) of sond waves in a broad freqency band (Hz-kHz). Since in this case the AVS is placed directly on the grond, only the DOA in the horizontal plane can be measred. An important challenge in sorce localization in this configration is the fact that the elevation angle of the incoming sond wave is distorted by grond reflections. It is therefore dificlt to determine the elevation angle accrately. This isse is addressed in paragraph 2. Any moving sorce will case a Doppler freqency shift and with passing propeller driven aircraft this effect is clearly noticed. The closest point of the aircraft (CPA) as well as the velocity of the aircraft can be determined from the Doppler shift. A method that can atomatically fit the Doppler signal of passing propeller driven aircraft is developed and is addressed briefly in paragraph 3. The DOA in the horizontal plane of the passing propeller driven aircraft can be measred accrately (a standard deviation of abot two degrees). The height of the aircraft can be estimated by combining this graph in combination with the Doppler graph. A last topic of the R&D is the classification of the acostic signatre of the aircraft. Some notes on the classification can be fond in paragraph 4. Apart from the development of the detection, classification and localization of aircraft, the acostic vector sensor is also in development for other applications. The AVS is for example sed for detecting and localizing rockets, artillery and mortars (RAM) [2]. The packaging is made sitable for long-term otdoor measrements. An example of a prototype an otdoor AVS is shown in Figre (right). This sensor has the capability of local processing and wireless commnication. This prototype has a fll PC bild in, next models will be operating on embedded hardware redcing the size and operating power. Apart from sing the AVS on the grond, the sensor is tested sccessflly on flying small (2kg class) fixed wing planes [4]. Also on these platforms it is possible to detect aircraft and implses from RAM sorces.
2. An estimation of the elevation angle An AVS is a small acostic sensor that is capable of determining the direction of arrival (DOA) of a sond sorce instantly from the relative amplitdes of the three orthogonal components and for the entire acostic bandwidth. However when the AVS is placed on the grond the normal component of the particle velocity is redced by the grond reflection. And the redction is nknown if the acostic impedance is nknown, see Figre. The particle velocity therefore cannot be sed for the measrement of the elevation angle. As an alternative the sond pressre signal in combination with the velocity signals in the horizontal plane is examined. Figre (left): a prototype of an acostic vector sensor for otdoor se. (Right) Incoming sond wave and reflected wave (ble), measred by a pressre sensor and two particle velocity sensors (red). The modeled sond field consists of an incoming and a reflected wave and the sensor has an arbitrary location on or above the grond. The incoming wave has an elevation angle θ, an azimth φ and it cases a pressre p at the sensor. The reflected wave cases a pressre of Rp, where the reflection coefficient R depends on the height of the sensor and the srface impedance. Assming plane waves, the expressions for the pressre and particle velocity are as follows at any time instant: p p + Rp Hence x p x y o cos ( p cos( θ )cos( φ) + Rp cos( θ )cos( φ) ) ( p cos( θ )sin( φ) + Rp cos( θ )sin( φ) ) y ( θ ) cos( φ) ; cos( θ ) sin( φ) p o () (2) The azimth and elevation can be compted directly from these eqations. 2. Impact of measrement errors The impact of measrement errors in the azimth is small. A maximm error of 3 degrees in the azimth angle is fond if the ratios between both x/p and y/p have an error of 5%. A larger impact is present in the near-horizontal elevation angles becase it is necessary to compte an inverse cosine to determine this angle. Since this fnction slope near, the near-horizontal elevation angles are difficlt to compte. This is illstrated in figre 2 which depicts the error bonds cased by small errors in x/p and y/p. It can be seen that the lower bond is limited by the fact that the sorce is assmed to be above the horizon. In the case where the error is %, errors of as mch as 8 degrees are fond for low elevations. However, the errors are considered acceptable from an elevation of abot 3 degrees, where the errors are or less in this case. 2
Figre 2. Error in compted elevation angle, cased by % (dark ble) and 5% (light ble) error in the ratio of velocity and pressre. Varios signal processing techniqes have been tested to find the average vales of x /p and y /p over a time interval and over all freqencies. The method that has shown to be the most robst is Principal Component Analysis. The atocorrelation matrix at time delay of the pressre and the two horizontal velocity components is estimated. Next, we calclate the eigenvale decomposition of this matrix. The eigenvector belonging to the largest eigenvale is a good estimate of the relation between pressre and the two horizontal velocity components which is independent of time and freqency. The angles are compted from this vector sing eqation 2. This approach is the maximm likelihood estimator in the presence of white, Gassian sensor noise, provided that the pertrbations are small. 2.2 Experimental Validation The goal of the experiments is to track the azimth and elevation of a propeller aircraft as it takes off (see figre 4b). The sensor is positioned below the flight path, m from the rnway at Tege International Airport in the Netherlands. The experimental setp consists of three Acostic Vector Sensors arranged in an eqilateral triangle with.5m side. Each of the probes is sed separately to compte the elevation angle and the reference reslt is obtained by applying conventional beamforming to the pressre signals. Measrement of a typical reslt is depicted in Figre 3. The azimth is determined accrately, and the remaining errors can be explained by slight misalignments of the probes. The elevation angle also clearly follows the reference reslt in cases where the elevation is higher than 3 degrees. Given the accracy of these reslts at the elevations above 3 degrees, it is conclded that the method considered in this article is certainly a viable way to track sorces. Figre 3. Azimth (left) and elevation (right) determined by three Acostic vector Sensors (red, green, ble). Given the accracy of these reslts at the elevations above 3 degrees, it is conclded that the method considered in this paragraph is certainly a viable way to track sorces for elevation angles higher than 3 degrees. 3
3. Estimation of velocity and distance Figre 4 shows the acostic spectrm of the passing propeller aircraft, inflenced by the Doppler effect. The x- and y- axis display time and freqency respectively. The spectral lines are cased by the harmonic behavior of the propeller. In the first few seconds the aircraft is approaching casing an elevated freqency in the last seconds the freqency is lowered becase the aircraft is moving away from the AVS. From the freqency shift the speed of the aircraft can be determined. With the slope of the spectral lines at approximately 3.7s the closest point of the aircraft (CPA) can be determined. A low CPA cases a steep slope. The velocity and closest point to the aircraft can be compted sing the Doppler effect. For this prpose it is assmed that the aircraft flies in a straight line, at a constant velocity. In this case, a model for the apparent freqency f i (t) measred from a stationary microphone is given by: 2 2 fac va ( t h / c) fi ( t) 2 2 c v 2 2 2 2 2 2 a vac ( t + h / c) h ( va c ) where f a sorce acostic freqency, c speed of sond in the medim, v a velocity of the aircraft (assmed sbsonic), h closest point of aircraft (CPA), t is the time. Atomated Doppler fitting software has been implemented and it has been shown to yield reslts accrate within a 5 percent in a nmber of earlier tests. This software With the above mentioned eqation of the Doppler shift the closest point of aircraft and the speed of the aircraft are determined to be 49m and 65km/h respectively. Althogh an accrate reference measrement is not available for this experiment, both of these vales have been fond to be accrate within a few percent in other tests. The heading can be determined from the azimth measrement, see figre 3 (left). (3) Figre 4. Time-freqency representation of a passing propeller aircraft 4. Frther research Frther research will focs on the detection of aircraft. Propeller aircraft have a niqe spectrm, which is expected to be detectable on long distances. Helicopters exhibit a similar spectrm, bt they tend to have a lower blade passing freqency. Jet aircraft are more difficlt to detect becase their spectra lack definite featres, sch that it is difficlt to distingish their sond from backgrond noise at long range. In this case, the Microflown sensor has a definite advantage over conventional sensors, making it possible to measre DOA at every freqency. Figre 5 depicts the response of a passing jet aircraft (left) and helicopter (right). Time and freqency are depicted horizontally and vertically respectively. The brightness indicates the sond level and the color indicates the direction of arrival. Althogh the spectrm contains very few featres, it can be seen clearly that there is a moving broadband sorce. Any broadband sorce which has the same angle at all freqencies which has a nonzero elevation is likely to be a jet aircraft. 4
These algorithms are crrently in the early stages of testing. Althogh it is considered nlikely that a single acostic vector sensor can detect an aircraft consistently at a distance of several kilometers, a network of sensors is likely to be able to do a mch better job. Figre 5. (Left) time-freqency-angle plot of a passing F6 jet aircraft, (right) time-freqency-angle plot of a passing helicopter (middle): legenda. Color indicates the direction 5. CONCLUSIONS An acostic vector sensor (AVS) is capable to determine the direction of arrival of sond waves of varios signatres. At first instance the AVS is packaged in sch way that it can be sed otdoors on the grond, sch realization is called the nattended grond sensor UGS. At a lower readiness level the AVS is also tested on nmanned aerial vehicle s (UAV) and grond vehicles. The UGS is sed for many applications varying from battlefield acostics (localization of rockets artillery, mortars, snipers, gnshots etc.); environmental noise localization to, the topic of this paper, detection, localization and tracking of aircraft. Several aircraft are measred and several methods of localization have been tested. In order to atomate the process the signatres of aircraft have to be classified. This is done for helicopter noise and is worked on for propeller and jet noise. The tracking of aircraft can be done reasonable accrate in real time if the elevation angle is larger than 3 degrees. REFERENCES [] Hans-Elias de Bree, Jelmer Wind, Sbramaniam Sadasivan, Broad banded acostic vector sensors for otdoor monitoring propeller driven aircraft, DAGA, 2 [2] Dr. Ir. Hans-Elias de Bree, Dr. Ir. Jelmer Wind, Prof. Dr. Ir. Erik Dryvesteyn, mlti prpose acostic vector sensors for battlefield acostics, a passive sensor to detect mlti events that can be sed on mltiple platforms, DAMA, 2 [3] J. Kots, A. Czyzewski Acostic radar employing particle velocity sensors, Advances in Soft Compting, 2 [4] E. Tijs, G.C.H.E. de Croon, J. Wind, B. Remes, C. de Wagter, H.E. de Bree, R. Rijsink, Hear & avoid for micro air vehicles, IMAV, 2 5