METHOD FOR HEIGHT ESTIMATION OF OBJECTS USING ULTRASOUND SENSORS

Description

[0001] The invention relates to a method for estimating the height of objects in the vicinity of vehicles using ultrasonic sensors.

[0002] It is known to use ultrasonic sensors to gather environmental information around a vehicle, for example, to determine the distance to other objects when parking. Ultrasonic sensors provide distance information based on the travel time of the ultrasonic signal, but not direct height information of the detected object, as the angle from which the back reflection occurs cannot be determined.

[0003] However, it is known to determine the height of the object from which the reflection occurs by evaluating the geometric relationships from several transmit-receive cycles. For example, if the vehicle moves between two transmit-receive cycles, the height of the object can be calculated by evaluating the measured distance information between the ultrasonic sensor and the reflecting object, and a distance information that specifies the horizontal distance between the sensor positions of the ultrasonic sensor along the propagation direction of the ultrasonic signal between the ultrasonic sensor and the reflecting object.

[0004] Such a method is known, for example, from DE 101 51 965 A1. Similar methods can be found in DE 10 2018 218007 A1 and in DE 10 2014 114999 A1.

[0005] The problem is that noise often leads to poor measurement results, resulting in inadequate height estimation with high deviations.

[0006] Based on this, the object of the invention is to provide a method for estimating the height of objects in the vicinity of vehicles using ultrasonic sensors, which allows a reliable estimation of the height of the reflecting object.

[0007] The problem is solved by a method having the features of independent claim 1. Preferred embodiments are the subject of the dependent claims. A system for estimating the height of an object is the subject of dependent claim 15.

[0008] According to a first aspect, the invention relates to a method for estimating the height of an object using ultrasonic sensors on a vehicle. The method comprises the following steps: First, at least two ultrasonic signals are received by at least one ultrasonic sensor. A single ultrasonic sensor can have different sensor positions relative to the object due to vehicle movement. In other words, the received information from a single ultrasonic sensor is evaluated, which, due to the vehicle movement, assumes different positions relative to the object whose height is to be determined during successive measurement cycles. Alternatively, several ultrasonic sensors can receive the at least two ultrasonic signals, having different sensor positions relative to the object due to vehicle movement and / or different arrangements on the vehicle.

[0009] Subsequently, an initial height value is calculated, which is a measure of the object's squared height. The object's height is preferably its relative height to the installation height of at least one ultrasonic sensor on the vehicle. In other words, the object's height is not directly determined, but rather its squared height, in order to avoid inaccuracies caused by noise. The initial height value is calculated based on two distance measurements taken between the respective sensor positions and the object, and one horizontal distance measurement taken between the sensor positions. This initial height value is determined, for example, in a first measurement cycle.

[0010] The variance of the first height information is then calculated.

[0011] Subsequently, at least one further ultrasonic signal is received by the at least one ultrasonic sensor. Based on this additional ultrasonic measurement, a second height measurement is calculated, which is a measure of the squared height of the object. This calculation is again based on two distance measurements taken between the respective sensor position and the object, and one horizontal distance measurement taken between the sensor positions. At least some of the information required for the calculation comes from the additional ultrasonic measurement, which, for example, constitutes a second measurement cycle. The second measurement cycle can be one that immediately follows the first measurement cycle, or there can be further measurement cycles between the first and second measurement cycles.For example, if the first and second measurement cycles are not immediately consecutive, the vehicle travels a longer distance between the first and second measurement cycles, which increases the accuracy of the height estimation.

[0012] The variance of the second height information is then calculated.

[0013] In a further step, an averaged height information is calculated by combining the first and second height information, and an averaged variance of the height information is calculated by combining the variance of the first and second height information.

[0014] The classification of a detected object into a height class is carried out by calculating at least one probability value based on a normal distribution function, which has the averaged height information as its mean and the averaged variance of the height information as its variance.

[0015] The technical advantage of the method according to the invention lies in the fact that a reliable determination of the height of the reflecting object is achieved by determining height information that takes into account the squared height of the object. This results, upon repeated application, in a distribution of height information values ​​that more closely resembles a normal distribution than when the unsquared height of the object is determined directly.

[0016] According to one embodiment, further height information (i.e., in addition to the first and second height information, supplementary height information) is iteratively calculated. This additional height information is a measure of the squared height of the object, along with variance information for this supplementary height information. The averaged height information is determined by combining the height information, preferably all iteratively determined height information, and an averaged variance of the height information is determined by combining the variances of the height information, preferably all iteratively determined variances. By iteratively determining a multitude of height information and their variances and combining this height information, a reliable classification of the object's height can be achieved.

[0017] According to one embodiment, the first, second and / or further height information is calculated using the following formula: H = h 2 = r 1 2 − r 1 2 − r 2 2 + s 2 2 4 s 2 ; where: h: Height difference between the at least one ultrasonic sensor and the object; r 1 : Distance between a first transmitter position and the object in the transmission and reception direction; r 2 : Distance between a second transmitter position and the object in the transmission and reception direction; s : Distance information measured in the horizontal direction as the distance between the first and second sensor positions.

[0018] Unlike the direct determination of the height difference h, the aforementioned formula does not contain a square root term, which means that negative values ​​of H or the squared height h, which can arise from noise, do not lead to invalid results.

[0019] According to one embodiment, the variance of the first, second, and / or subsequent height information is determined based on a first-order variational analysis. Preferably, the variational analysis calculates the variance of the height information by adding several summands, each summand taking into account the change in the height information as a function of the change in an input variable used to calculate the height information.

[0020] According to one embodiment, the variance of the first, second and / or further height information is calculated using the following equation: Var H = dH dr 1 2 ⋅ Var r 1 + dH dr 2 2 ⋅ Var r 2 + dH ds 2 ⋅ Var s ; where: r1: distance between a first transmitter position and the object in the transmission and reception direction; r2: distance between a second transmitter position and the object in the transmission and reception direction; s: distance information measured in the horizontal direction as the distance between the first and second sensor positions; dH dr 1 : first derivative of the height information H with respect to r 1 ; dH dr 2 : first derivative of the height information H with respect to r 2 ; dH ds : first derivative of the height information H with respect to s; Our [ r 1 ]: Variance of the distance between a first transmitter position and the object in the transmitting and receiving directions; Our [ r 2 ]: Variance of the distance between a second transmitter position and the object in the transmitting and receiving directions; Our [ s ]: Variance of the distance information measured in the horizontal direction as the distance between the first and second sensor positions.

[0021] According to one embodiment, the average height information is calculated based on the following formula: H ¯ = Var H " ⋅ H ′ + Var H ′ ⋅ H " Var H ′ + Var H " ; where: H': Estimated height information from a first measurement cycle; H": Estimated height information from a second measurement cycle; Var[H']: Variance of the height information in the first measurement cycle; Var[H"]: Variance of the height information in the second measurement cycle.

[0022] The estimated elevation information from the respective measurement cycles can either be derived from individual measurements or be averaged elevation information, i.e., itself derived from an average over several measurements. The same applies analogously to the variance of the elevation information in the first and / or second measurement cycle.

[0023] According to one embodiment, the average variance of the height information is calculated based on the following formula: Var H ¯ = 1 1 Var H ′ + 1 Var H " ; where: Var[H']: Variance of the height information in the first measurement cycle; Var[H"]: Variance of the height information in the second measurement cycle.

[0024] According to another embodiment, the averaged height information and the averaged variance of the height information are calculated based on a least squares method. Weighting factors (weighted least squares method) can be used in this process, chosen to account for any correlation between the measurements.

[0025] According to one embodiment, the probability value for assigning the object to a height class is calculated based on the following formula: p = ∫ a b N x H ¯ Var H ¯ dx ; where: N ( x, H, Our [ H]): Normal distribution; a: lower limit for assignment to the respective altitude class; b: upper limit for assignment to the respective altitude class; H Average elevation information; Our [ H Average variance.

[0026] This allows the probability that an object is located within a height range defined by the lower or upper limit to be determined by assuming a normal distribution of the height information around the averaged height information as the mean and with a variance equal to the averaged variance.

[0027] According to one embodiment, the calculation of the altitude class is based on a correction function that takes into account the deviation of the statistical distribution of the altitude information from the normal function. This minimizes the error resulting from the deviation of the statistical distribution of the altitude information from the normal function.

[0028] According to one embodiment, the correction function is estimated based on a data series of height information determined from varying distance information between the respective sensor position and the object, and from varying horizontally measured distance information. In other words, the influence of the distance information on the statistical distribution of the height information is analyzed, and the correction function is selected accordingly.

[0029] According to one embodiment, a lower and / or upper limit used for calculating the probability value is adjusted based on the correction function. This allows the deviation of the statistical distribution of the height information from the normal function to be compensated for when determining the object's height by adapting the lower and / or upper limit.

[0030] According to one embodiment, the distance information is determined based on the vehicle's odometry data. In other words, the vehicle's odometry system can provide information indicating how the vehicle moved between two measurement cycles of the at least one ultrasonic sensor. Since this movement of the vehicle does not necessarily have to occur in the transmit or receive direction of the ultrasonic sensor, the distance information—i.e., the distance between the sensor positions in the transmit or receive direction of the ultrasonic sensor—must be calculated from the vehicle's odometry data.

[0031] According to one embodiment, the object is assumed to be a line object with a longitudinal orientation, and the transmit and receive direction of the at least one ultrasonic sensor and the direction in which the distance information is measured are assumed to be perpendicular to this longitudinal orientation of the line object.

[0032] According to an alternative embodiment, the object is represented by an object contour line using information obtained through the ultrasonic sensor in several detection cycles, and the distance information is assumed to be the difference between the horizontally measured distance of the sensor positions to this line.

[0033] According to another aspect, the invention relates to a system for estimating the height of an object comprising an ultrasonic sensor system provided on a vehicle and a computer unit, wherein the system is configured to perform the following steps: a) Receiving at least two ultrasonic signals by at least one ultrasonic sensor of the ultrasonic sensor system, wherein a single ultrasonic sensor has different sensor positions relative to the object due to vehicle movement, or wherein several ultrasonic sensors have different sensor positions relative to the object due to vehicle movement and / or a different arrangement on the vehicle; b) Calculating an initial height measurement, which is a measure of the squared height of the object, based on two distance measurements taken between the respective sensor positions and the object, and a horizontal distance measurement taken between the sensor positions by the processing unit; c) Calculating the variance of the initial height measurement by the processing unit;d) Receiving at least one further ultrasonic signal by the at least one ultrasonic sensor and calculating a second height information, which is a measure of the squared height of the object, based on two distance information measurements taken between the respective sensor positions and the object, and one horizontal distance measurement taken between the sensor positions; e) Calculating the variance of the second height information; f) Calculating an averaged height information by combining the first and second height information and an averaged variance of the height information by combining the variances of the first and second height information; g) Classifying a detected object into a height class by calculating at least one probability value by the processing unit based on a normal distribution function that has the averaged height information as its mean and the averaged variance of the height information as its variance.

[0034] The terms "approximately", "essentially" or "about" mean, within the meaning of the invention, deviations from the respective exact value by + / - 10%, preferably by + / - 5% and / or deviations in the form of changes that are insignificant for the function.

[0035] Further developments, advantages, and possible applications of the invention will also become apparent from the following description of exemplary embodiments and from the figures. All features described and / or illustrated are, individually or in any combination, fundamentally the subject matter of the invention, irrespective of their compilation in the claims or their cross-reference. The content of the claims is also incorporated into the description.

[0036] The invention will be explained in more detail below with reference to exemplary embodiments shown in the figures. The figures show: Fig. 1 shows, by way of example and schematically, a vehicle equipped with ultrasonic sensors comprising several ultrasonic sensors distributed around the vehicle's circumference and a computer unit for evaluating the information provided by the ultrasonic sensors. Fig. 2 shows, by way of example and schematically, the detection of an environmental object by an ultrasonic sensor from two different sensor positions; Fig. 3 shows, by way of example and schematically, a histogram showing the statistical distribution of the height information H; and Fig. 4 shows, by way of example, a flowchart illustrating the steps of a procedure for determining the height of an object.

[0037] Figure 1 Figure 1 shows an exemplary and roughly schematic representation of a vehicle 1. The vehicle 1 has a large number of ultrasonic sensors 2, by means of which environmental detection is effected.

[0038] The ultrasonic sensors 2 are coupled with at least one computing unit 4, by means of which the following described method for estimating the height of an object 3 in the vicinity of a vehicle 1 is carried out.

[0039] Figure 2 Figure 1 shows an example of a detection situation in which an object 3, which is lower than the installation height of the ultrasonic sensor 2 on the vehicle 1, is detected by means of an ultrasonic sensor 2 of a vehicle 1.

[0040] The height of object 3 can be determined by either taking multiple measurements with a single ultrasonic sensor 2, for example, by taking a first measurement at a first sensor position P1 and a second measurement at a second sensor position P2, where sensor positions P1 and P2 differ due to the movement of vehicle 1. Alternatively, the height of object 3 can also be determined by at least two measurements from different ultrasonic sensors 2 of the vehicle, which are arranged at different positions on vehicle 1 and thus have different distances to object 3.

[0041] As in Fig. 2As shown, the ultrasonic sensor 2, located at the first sensor position P1, determines an initial distance measurement r1. This initial distance measurement r1 corresponds to the distance measured in a direct line of sight between the ultrasonic sensor 2 at position P1 and the object 3. Similarly, the ultrasonic sensor 2, located at the second sensor position P2, determines a second distance measurement r2. This second distance measurement r2 corresponds to the distance measured in a direct line of sight between the ultrasonic sensor 2 at position P2 and the object 3.

[0042] The horizontal distance measured along the line connecting sensor 2 and object 3 between the first and second sensor positions p1, p2 is hereinafter referred to as distance information s. The vertically measured height difference between object 3 and ultrasonic sensor 2 is hereinafter referred to as height h.

[0043] Based on geometric relationships, the height h can be calculated as follows: h = r 1 2 − r 1 2 − r 2 2 + s 2 2 4 s 2 This includes: h: Height difference between the at least one ultrasonic sensor and the object; r 1 : Distance between a first transmitter position and the object in the transmission and reception direction; r 2 : Distance between a second transmitter position and the object in the transmission and reception direction; s : Distance information measured in the horizontal direction as the distance between the first and second sensor positions.

[0044] The problem is that noise can cause the term under the square root to become negative, making it impossible to calculate the height.

[0045] The following reveals a method for the height classification of object 3 that avoids the problem of the negative term under the square root.

[0046] The method according to the invention estimates a height information H, which corresponds to the square of the height h, instead of the height h. H = h 2 = r 1 2 − r 1 2 − r 2 2 + s 2 2 4 s 2

[0047] This again includes: h: Height difference between the at least one ultrasonic sensor and the object; r 1 : Distance between a first transmitter position and the object in the transmission and reception direction; r 2 : Distance between a second transmitter position and the object in the transmission and reception direction; s : Distance information measured in the horizontal direction as the distance between the first and second sensor positions.

[0048] Since individual measurements can be highly error-prone and thus lead to incorrect height estimates, several measurements are carried out and a height estimate of object 3 or a height classification is made based on an averaging of the estimated height information H and the estimation of the variance of the height information H.

[0049] To determine the variance of the height information H, for example a first order variational analysis is performed.

[0050] This can be done, for example, based on the following formula: Var H = dH dr 1 2 ⋅ Var r 1 + dH dr 2 2 ⋅ Var r 2 + dH ds 2 ⋅ Var s

[0051] Where: r1: distance between a first transmitter position and the object in both the transmitting and receiving directions; r2: distance between a second transmitter position and the object in both the transmitting and receiving directions; s: horizontally measured distance information as the distance between the first and second sensor positions; dH dr 1 : first derivative of the height information H with respect to r 1 ; dH dr 2 : first derivative of the height information H with respect to r 2 ; dH ds : first derivative of the height information H with respect to s; Our [ r 1 ]: Variance of the distance between a first transmitter position and the object in the transmitting and receiving directions; Our [ r 2 ]: Variance of the distance between a second transmitter position and the object in the transmitting and receiving directions; Our [ s ]: Variance of the distance information measured in the horizontal direction as the distance between the first and second sensor positions.

[0052] The first derivative of the height information H with respect to r 1 is calculated as follows: dH dr 1 = 2 r 1 − r 1 r 1 2 − r 2 2 + s 2 s 2

[0053] The first derivative of the height information H with respect to r 2 is calculated as follows: dH dr 2 = r 2 r 1 2 − r 2 2 + s 2 s 2

[0054] The first derivative of the height information H with respect to s is calculated as follows: dH ds = r 1 2 − r 2 2 + s 2 2 − 2 s 2 r 1 2 − r 2 2 + s 2 2 s 3

[0055] Advantageously, several measurements taken by the vehicle's ultrasonic sensors, for example during object tracking while the vehicle is moving, are combined. The respective variance of the height information H can then be used as a weighting factor.

[0056] In the event that a first height information H' and a second height information H" are determined, an average height information can be determined using the following formula: H ¯ = Var H " ⋅ H ′ + Var H ′ ⋅ H " Var H ′ + Var H " This includes: H': first estimated height information from a first measurement cycle; H": second estimated height information from a first measurement cycle; Var[H']: variance of the height information in the first measurement cycle; Var[H"]: variance of the height information in the second measurement cycle.

[0057] The average variance can be calculated as follows: Var H ¯ = 1 1 Var H ′ + 1 Var H " where: Var[H']: Variance of the height information in the first measurement cycle; Var[H"]: Variance of the height information in the second measurement cycle.

[0058] It should be noted that the height information H', H" and the variances Var[H'] and Var[H"] can each refer to a single measurement cycle (i.e., determination of a single height information H by measuring distance information through a sensor at two different sensor positions) but also to several measurement cycles, i.e., the height information H', H" and the variances Var[H'] and Var[H"] can themselves be averaged values.

[0059] Alternatively, combining height measurements H can also be accomplished using a weighted least squares method. The weighting factors of such a method can be chosen to account for any existing correlation between the two measurements.

[0060] Once a large amount of elevation information H has been determined, the elevation h of object 3 can be calculated based on this information. In particular, object 3 can be classified into an elevation class.

[0061] For example, a height classification can be carried out by checking the probability that object 3 has a height h within a certain height range.

[0062] In the case that the height class is defined by a lower limit a and an upper limit b, the probability that the height of object 3 falls into the height class can be calculated using the following formula: p = ∫ a b N x H ¯ Var H ¯ dx

[0063] The following applies: N ( x,H, Our [ H ]): Normal distribution of H over x with a variance Our [ H ]; a: lower limit for assignment to the respective altitude class; b: upper limit for assignment to the respective altitude class; H Average elevation information; Our [ H ]:averaged variance.

[0064] If the altitude class is not limited downwards or upwards, i.e., it is the lowest or highest altitude class, the lower limit a can take the value -∞ and the upper limit b the value +∞.

[0065] It is understood that the limit values ​​a, b of formula 9 must also be squared due to the relationship H = h 2< , i.e. a classification limit of 0.3m must be converted into a limit value of 0.09m 2< .

[0066] Formula 9 assumes that the averaged height information has a uniform distribution over x. In reality, however, the averaged height information often deviates from a normal distribution.

[0067] Fig. 3 This shows the actual distribution of the height information H based on a histogram, where the actual height h of the object relative to the sensor was 0.1 m. As can be seen, the distribution is not symmetrical about a vertical axis, so the height information H is not normally distributed.

[0068] To compensate for this deviation, at least one limit value a, b can be adjusted using a correction function. In particular, a correction function can be chosen that adjusts at least one limit value depending on the distance information r1, r2 and the distance information s. Such a correction function can be determined, for example, through a simulation or from real data based on which the dependence of the height information H on the distance information r1, r2 and the distance information s is determined.

[0069] As previously described, the distance information s, i.e. the change in the sensor positions P1, P2 along the transmit and receive direction of the ultrasound signal, is required.

[0070] The vehicle's movement itself can be determined using information from the vehicle's odometry unit. However, the vehicle's direction of movement does not necessarily coincide with the direction of transmission and reception of the ultrasonic signal between the ultrasonic sensor and the object.

[0071] The distance information s can be estimated, for example, as follows: Object 3 can be assumed to be a line object. The line object is assumed to be oriented relative to the transmit and receive direction of the ultrasonic sensor 2 such that the transmit and receive direction of the ultrasonic sensor 2 is perpendicular to the longitudinal axis of the line object. This also implies that the distance information s is to be measured perpendicular to the longitudinal axis of the line object. If the direction of movement of vehicle 1 and its absolute motion are known, the distance information s can be calculated from this.

[0072] Alternatively, the object contour can be determined as a curved or arbitrarily shaped line, or as a polygon or polygon segment, through multiple measurements and tracking. In this case, the distance information s can be calculated directly as the difference between the respective sensor positions P1 and P2 and the line representing the object contour.

[0073] Fig. 4 The figure shows in schematic form the steps of a method according to the invention for estimating the height of an object using ultrasonic sensors of a vehicle.

[0074] Initially, at least two ultrasonic signals are received by at least one ultrasonic sensor 2. A single ultrasonic sensor can have different sensor positions relative to the object due to vehicle movement. Alternatively, multiple ultrasonic sensors 2 can have different sensor positions relative to the object 3 due to vehicle movement and / or a different arrangement on the vehicle 1 (S10).

[0075] Subsequently, an initial height value H is calculated, which is a measure of the squared height h of the object. This calculation is based on two distance values ​​r1 and r2 measured between the respective sensor positions and the object 3, and a horizontal distance value s measured between the sensor positions (S11).

[0076] The variance of the first height information is then calculated (S12).

[0077] Subsequently, at least one further ultrasound signal is received by the at least one ultrasound sensor and a second height information is calculated, which is a measure of the squared height of the object, based on two distance information measured between the respective sensor position and the object and a distance information measured horizontally between the sensor positions (S13).

[0078] The variance of the second height information is then calculated (S14).

[0079] Subsequently, an averaged height information is calculated by combining the first and second height information, and an averaged variance of the height information is calculated by combining the variance of the first and second height information (S15).

[0080] Finally, a detected object is classified into a height class by calculating at least one probability value based on a normal distribution function, which has the mean of the averaged height information and the variance of the averaged variance of the height information (S16).

[0081] The invention has been described above using exemplary embodiments. It is understood that numerous modifications and adaptations are possible without thereby departing from the scope of protection defined by the patent claims. Reference sign list

[0082] 1 Vehicle 2 Ultrasonic sensor 3 Object hHeight HHHeight information pProbability value P1First sensor position P2Second sensor position r1First distance information r2Second distance information sDistance information

Claims

1. A method for the estimation of the height of an object (3) by means of an ultrasonic sensor system of a vehicle (1), comprising the following steps: a) receiving at least two ultrasonic signals by way of at least one ultrasonic sensor (2), wherein a single ultrasonic sensor (2) has different sensor positions relative to the object (3) due to a vehicle movement, or wherein multiple ultrasonic sensors (2) have different sensor positions (P1, P2) relative to the object (3) due to the vehicle movement and / or a different arrangement on the vehicle (1) (S10); b) calculating a first item of height information (H), which is a measure of the squared height (h) of the object, based on two items of distance information (r1, r2) measured between the respective sensor position (P1, P2) and the object (3) based on the at least two ultrasonic signals and an item of distance information (s) measured horizontally between the sensor positions (S11); c) calculating the variance of the first item of height information (S12); d) receiving at least one further ultrasonic signal by way of the at least one ultrasonic sensor (2) and calculating a second item of height information, which is a measure of the squared height (h) of the object, based on two items of distance information (r2, r3) measured between the respective sensor position (P2, P3) and the object (3), at least partially based on the at least one further ultrasonic signal, and an item of distance information (s) measured horizontally between the sensor positions (S13); e) calculating the variance of the second item of height information (S14); f) calculating an averaged item of height information by combining the first and second item of height information and an averaged variance of the item of height information by combining the variance of the first and second item of height information (S15); g) classifying a detected object (3) into a height class by calculating at least one probability value (p) based on a normal distribution function, which has the averaged item of height information as a mean value and the averaged variance of the item of height information as a variance (S16).

2. The method as claimed in claim 1, characterized in that further height information (H), which is a measure of the squared height (h) of the object, and variance information relating to this further height information are calculated iteratively, and in that the averaged item of height information is determined by combining the height information and an averaged variance of the height information is determined by combining the variances of the height information.

3. The method as claimed in claim 1 or 2, characterized in that the first, second, and / or further item of height information (H) is calculated by the following formula: H = h 2 = r 1 2 − r 1 2 − r 2 2 + s 2 2 4 s 2 ; wherein the following applies: h: height difference between the at least one ultrasonic sensor and the object; r1: distance between a first transmitter position and the object in the transmitting and receiving directions; r2: distance between a second transmitter position and the object in the transmitting and receiving directions; s: item of distance information measured in the horizontal direction as the distance between the first and second sensor positions.

4. The method as claimed in claim 1 or 2, characterized in that the variance of the first, second, and / or further item of height information is ascertained based on a first-order variation analysis.

5. The method as claimed in any one of the preceding claims, characterized in that the calculation of the variance of the first, second, and / or further item of height information (H) is carried out by the following equation: Var H = dH dr 1 2 ⋅ Var r 1 + dH dr 2 2 ⋅ Var r 2 + dH ds 2 ⋅ Var s ; wherein the following applies: r1: distance between a first transmitter position and the object in the transmitting and receiving directions; r2: distance between a second transmitter position and the object in the transmitting and receiving directions; s: item of distance information measured in the horizontal direction as the distance between the first and second sensor positions; dH dr 1 : first derivative of the item of height information H according to r1; dH dr 2 : first derivative of the item of height information H according to r2; dH ds : first derivative of the item of height information H according to s; Var[r1]:variance of the distance between a first transmitter position and the object in the transmitting and receiving directions; Var[r2]:variance of the distance between a second transmitter position and the object in the transmitting and receiving directions; Var[s]: variance of the distance information measured in the horizontal direction as the distance between the first and second sensor positions.

6. The method as claimed in any one of the preceding claims, characterized in that the calculating of the averaged item of height information is carried out based on the following formula: H ¯ = Var H " ⋅ H ′ + Var H ′ ⋅ H " Var H ′ + Var H " ; wherein the following applies: H': estimated item of height information from a first measurement cycle; H": estimated item of height information from a second measurement cycle; Var[H']: variance of the item of height information in the first measurement cycle; Var[H"]: variance of the item of height information in the second measurement cycle.

7. The method as claimed in any one of the preceding claims, characterized in that the calculating of the averaged item of height information is carried out based on the following formula: Var H ¯ = 1 1 Var H ′ + 1 Var H " ; wherein the following applies: Var[H']: variance of the item of height information in the first measurement cycle; Var[H"]: variance of the item of height information in the second measurement cycle.

8. The method as claimed in any one of claims 1 to 5, characterized in that the calculating of the averaged height information and of the averaged variance of the item of height information is carried out based on a method of averaged least square errors.

9. The method as claimed in any one of the preceding claims, characterized in that the calculating of the probability value (p) for assignment of the object to a height class is carried out based on the following formula: p = ∫ a b , N x H ¯ Var H ¯ dx ; wherein the following applies: N(x,H,Var[H]): normal distribution; a: lower limit value for assignment to the respective height class; b: upper limit value for assignment to the respective height class; H: averaged item of height information; Var[H]: averaged variance.

10. The method as claimed in any one of the preceding claims, characterized in that the calculation of the height class is based on a correction function which takes into consideration the deviation of the statistical distribution of the item of height information (H) from the normal function.

11. The method as claimed in claim 10, characterized in that the correction function is estimated based on a data series of height information (H) which has been ascertained based on different distance information between the respective sensor position (P1, P2) and the object (3) and different horizontally measured distance information (s).

12. The method as claimed in claim 10 or 11, characterized in that a lower and / or upper limit value used for the calculation of the probability value (p) is adapted based on the correction function.

13. The method as claimed in any one of the preceding claims, characterized in that the object (3) is assumed to be a line object having a longitudinal orientation and the transmitting and receiving directions of the at least one ultrasonic sensor (2) and the direction in which the distance information (s) is measured are assumed to be perpendicular to this longitudinal alignment of the line object.

14. The method as claimed in any one of claims 1 to 12, characterized in that the object (3) is replicated by an object contour line by means of information that has been ascertained by the ultrasonic sensor system in multiple detection cycles, and the distance information (s) is assumed to be the difference between the horizontally measured distance of the sensor positions (P1, P2) and the line.

15. A system for the estimation of the height of an object (3), comprising an ultrasonic sensor system provided on a vehicle (1) and a computer unit (4), wherein the system is designed to carry out the following steps: a) receiving at least two ultrasonic signals by way of at least one ultrasonic sensor (2) of the ultrasonic sensor system, wherein a single ultrasonic sensor (2) has different sensor positions (P1, P2) relative to the object (3) due to a vehicle movement, or wherein multiple ultrasonic sensors (2) have different sensor positions (P1, P2) relative to the object (3) due to the vehicle movement and / or a different arrangement on the vehicle (1); b) calculating a first item of height information (H), which is a measure of the squared height (h) of the object, based on two items of distance information measured between the respective sensor position (P1, P2) and the object (3) based on the at least two ultrasonic signals and an item of distance information (s) measured horizontally between the sensor positions (P1, P2) by the computer unit (4); c) calculating the variance of the first item of height information (H) by way of the computer unit (4); d) receiving at least one further ultrasonic signal by way of the at least one ultrasonic sensor (2) and calculating a second item of height information, which is a measure of the squared height (h) of the object, based on two items of distance information (r2, r3) measured between the respective sensor position (P2, P3) and the object (3), at least partially based on the at least one further ultrasonic signal, and an item of distance information (s) measured horizontally between the sensor positions; e) calculating the variance of the second item of height information; f) calculating an averaged item of height information by combining the first and second item of height information and an averaged variance of the item of height information by combining the variance of the first and second item of height information; g) classification of a detected object (3) into a height class by calculating at least one probability value (p) by way of the computer unit (4) based on a normal distribution function, which has the averaged item of height information as a mean value and the averaged variance of the item of height information as a variance.