Range measurement

Abstract

A phase-based range measurement solution is provided, comprising (i) determining multiple phase differences, each phase difference being based on a pair of phase measurements; (ii) determining an overall phase difference based on the multiple phase differences, each phase difference being weighted; and (iii) determining the range based on the overall phase difference.

Description

Technical field

[0001] This disclosure generally relates to technologies for positioning and range determination using wireless signals. background

[0002] As described in [P. Zand, J. Romme, J. Govers, F. Pasveer and G. Dolmans, “A high-accuracy phase-based ranging solution with Bluetooth Low Energy (BLE)”, 2019 IEEE Wireless Communications and Networking Conference (WCNC), 2019, pp. 1-8, doi: 10.1109 / WCNC.2019.8885791], multi-carrier phase difference (MCPD) is a transmitter-to-transmitter ranging solution used in various technologies. In the Bluetooth standard, MCPD is used for high-accuracy distance measurement (HADM), also known as channel sounding (CS), to locate the position of a Bluetooth device. MCPD uses a series of phase measurements across multiple frequency channels. This localization is also referred to as MCPD range determination.

[0003] MCPD range determination uses an initiator (also called the master) and a reflector (also called the slave). The initiator is the device that starts the range determination procedure, and the reflector is the responding device.

[0004] Once two devices have established a connection, the initiator transmits an unmodulated constant tone, a local oscillator (LO) signal, to the reflector on a first channel. The reflector performs a phase measurement Φ. R on the received carrier, it transmits a constant tone, i.e., its LO, back to the initiator on the same channel. The initiator then performs a phase measurement Φ. I through.

[0005] This procedure is performed on a number of K f-Channels repeatedly. At the end of the procedure, the reflector sends measurement results across the entire frequency band to the initiator, enabling the initiator to calculate the range (see also US 9,274,218 B2).

[0006] The phase measurements across the channels are referred to as: Φ[k]=ΦI[k]+ΦR[k], k=0,1,...,Kf−1

[0007] A range r can be calculated as follows: r=c02⋅Δω⋅mean(ΔΦ[1],ΔΦ[2],...ΔΦ[Kf−1]) where ΔΦ[k]=Φ[k]−Φ[k−1] a phase difference between adjacent channels.

[0008] Equation (2) represents the final step of the range determination algorithm described in [P. Zand, J. Romme, J. Govers, F. Pasveer and G. Dolmans, “A high-accuracy phase-based ranging solution with Bluetooth Low Energy (BLE)”, 2019 IEEE Wireless Communications and Networking Conference (WCNC), 2019, pp. 1–8, doi: 10.1109 / WCNC.2019.8885791]. However, this approach only uses phase differences between adjacent channels, resulting in reduced range determination accuracy.

[0009] The same range determination algorithm can be applied in radar systems based on the step frequency continuous wave (SFCW) method.

[0010] The task is to provide an improved solution, in particular improved range determination accuracy for systems that use phase measurement information. Brief description of the drawings

[0011] Embodiments are shown and illustrated with reference to the drawings. The drawings serve to illustrate the basic principle, so only aspects necessary for understanding the basic principle are depicted. The drawings are not to scale. In the drawings, the same reference numerals denote the same features. Fig. Figure 1 shows a diagram that displays a total number of K f = 8 channels, including two pairings. Fig. 2 shows a diagram that shows a total number of K f = 8 channels with four pairs, where each pair combines two channels. Fig. Figure 3 shows a diagram that displays a total number of K f = Includes 8 channels that visualize different distances d of equidistant pairings. Fig. Figure 4 shows an example of an extended equidistant pairing based on subdiagram 304 of Fig. 3. Fig. Figure 5 shows a diagram illustrating the FAR-MP category, which uses equidistant peak-to-peak (or valley-to-valley) pairing. Fig. Figure 6 shows a diagram illustrating the MID-MP category, which uses equidistant peak-to-trough pairing. Fig. Figure 7 shows a diagram illustrating the NEAR-MP category, which includes an amplitude of the IQ sampling values ​​across the channels. Fig. Figure 8 shows a diagram illustrating the NEAR-MP category with a limited range for mating patterns. Fig. Figure 9 illustrates an exemplary flowchart of a procedure for operating a device for performing area measurements. Fig. Figure 10 shows an example block diagram that visualizes different use cases for a system implementation that uses range measurements. Fig. Figure 11 illustrates a block diagram of a system that can be used for range measurement. Detailed description

[0012] One notation for phase variables is as follows: Φ - non-italic, non-bold - deterministic unwrapped phase Φ - non-italic, bold - deterministic wrapped phase Φ italic, non-bold - stochastic unwrapped phase Φ italic, bold - stochastic wrapped phase

[0013] Therefore, the following applies: Φ=Φ(mod 2π)

[0014] It is noted that the term "increasing accuracy" refers specifically to reducing the standard deviation of the range measurement. Furthermore, the term "deviation" refers to "standard deviation," which in particular assumes a normal (e.g., random) distribution. Legacy approach

[0015] Reference is made to [P. Zand, J. Romme, J. Govers, F. Pasveer and G. Dolmans, “A high-accuracy phase-based ranging solution with Bluetooth Low Energy (BLE)”, 2019 IEEE Wireless Communications and Networking Conference (WCNC), 2019, pp. 1-8, doi: 10.1109 / WCNC.2019.8885791].

[0016] The wrapped-phase measurement of each channel is referred to as: Φ[k], k=0,1,...,Kf−1, with a total number of channels K f and a channel index k. A frequency of channel k is defined as ω[k]=ω0+k⋅Δω, where ω0 is a carrier frequency of the 0- ten (first) channel and Δω is a frequency difference between adjacent channels.

[0017] Next, a phase difference between adjacent channels is determined: ΔΦ[k]=Φ[k]−Φ[k−1], k=1,2,...,Kf−1

[0018] For a valid range measurement with MCPD range determination, the phase difference between all adjacent channels is preferably less than 2π, i.e., ΔΦ[k]<2π, for any k.

[0019] Therefore, the unwrapped phase difference is the same as the wrapped one, i.e.: ΔΦ[k]=ΔΦ[k], for any k.

[0020] In [P. Zand, J. Romme, J. Govers, F. Pasveer and G. Dolmans, “A high-accuracy phase-based ranging solution with Bluetooth Low Energy (BLE)”, 2019 IEEE Wireless Communications and Networking Conference (WCNC), 2019, pp. 1-8, doi: 10.1109 / WCNC.2019.8885791] it is noted that the range is directly proportional to the phase difference between any two adjacent channels: r=−c02⋅Δω⋅ΔΦ[k], for an arbitrary k, where c0 is the speed of light.

[0021] Therefore, the area consisting of two adjacent channels can be calculated using equation (9).

[0022] The accuracy of the range measurement is increased by using an average of all phase differences: ΔΦavg=mean(ΔΦ[1],ΔΦ[2],...,ΔΦ[Kf−1])

[0023] The area is then equal r=−c02⋅Δω⋅ΔΦavg Exemplary embodiments

[0024] The examples described herein may be based on a stochastic analysis, i.e., treating the phase measurement errors as random (or randomized) variables.

[0025] The standard deviation of phase measurements is directly proportional to the standard deviation of range measurements. The examples described here aim to reduce this deviation, thereby increasing the accuracy of the range measurement.

[0026] The phase measurement Φ[k] of each channel can be modeled as a (e.g. random) variable with a normal (Gaussian) probability distribution. Φ[k]∼N(μ[k], σ2[k]), μ[k]=Φ[k]

[0027] It is assumed that the mean of the distribution essentially corresponds to the deterministic phase measurement.

[0028] The following assumptions are made: (a) The phase measurement of each channel has the same standard deviation σ, i.e. σ[k] = σ, for any k. (b) There is no cross-correlation ρ in phase measurements between any two channels, i.e. ρ[m, n] = 0, m, n = 1, 2, ... , K f - 1, (m ≠ n).

[0029] Therefore, the last notation for stochastic wrapped-phase measurement is Φ[k]∼N(μ[k], σ2), μ[k]=Φ[k].

[0030] Furthermore, an unwrapped phase has the same deviation as a wrapped phase, i.e.: Φ[k]∼N(μ[k], σ2), μ[k]=Φ[k].

[0031] The following assumptions are a starting point made for the purpose of rationalizing stochastic analysis, but are not intended to limit the cases to which the approach presented herein can be applied.

[0032] A stochastic analysis can be applied to the ΔΦ avg The term of equation (10) can be applied. This average of all phase differences is directly proportional to the range r, as shown in equation (11). Example algorithm

[0033] To use phase measurements from all channels, the following approach can be used:

[0034] The phase difference between adjacent channels is determined as follows: ΔΦ[k]=Φ[k]−Φ[k−1], k=1,2,...,Kf−1

[0035] The phase across all channels is unwrapped by a cumulative summation of the phase differences: Φ[0]=0Φ[k]=Φ[0]+∑i=1kΔΦ[i],k=1,…,Kf−1

[0036] The starting point can be found at 0- ten A channel can be selected and it can be defined as 0. It is noted that any starting point can be used as long as phase differences between the channels are maintained.

[0037] It is noted that phase differences are not limited to adjacent channels.

[0038] The unwrapping carried out in equation (15) makes it possible to take the phase difference between any two channels as a separate area measurement.

[0039] Next, a scaled phase difference is introduced using a channel delta: ΔΦs[m,n]=Φ[n]−Φ[m]n−m=Φ[n]−Φ[m]d[m,n],n>m where the canal delta is defined as d[m,n]=n−m

[0040] A range r can be calculated from the scaled phase difference for any pair of m and n: r=−c02⋅Δω⋅ΔΦs[m,n]

[0041] The stochastic value of the scaled phase difference is: ΔΦs[m,n]=Φ[n]−Φ[m]n−m

[0042] Following the above assumptions (a) and (b), the deviation of the scaled phase difference is: σΔϕs=σ2+σ2n−m=σ⋅2n−m

[0043] The range r can be measured from the unwrapped phase difference between any two channels. Thus, any channel pair can correspond to an individual range measurement.

[0044] A deviation in the range measurement is directly proportional to the deviation in the scaled phase difference, which is inversely proportional to the channel delta of the m and n channel pair.

[0045] Furthermore, the deviation can be improved by using a mean value of several scaled phase differences, which is defined as an overall phase difference: ΔΦtot=mean(ΔΦs[m1,n1],ΔΦs[m2,n2],…)

[0046] The choice of m and n can have a significant impact in obtaining a suitable level of precision. Pairs with small channel deltas have a worse standard deviation according to equation (21).

[0047] In many cases, accuracy can be further improved by using a weighted average as follows: ΔΦtot=mean(g1⋅ΔΦs[m1,n1],g2⋅ΔΦs[m2,n2],…) where optimized weights (g1, g2, ...) can be determined according to [Handbook of Mathematics, 6th Edition

[2015] - IN Bronshtein , KA Semendyayev, Gerhard Musiol, Heiner Mühlig, page 854]. Alternatively, the optimized weights can be derived iteratively, as explained below.

[0048] The following examples can introduce a grouping of [m, n] channel pairs.

[0049] Therefore, a channel pair index u is defined: ΔΦs[mu,nu]=ΔΦs[u]d[mu,nu]=d[u] Example: Two channel pairs

[0050] Fig. Figure 1 shows a diagram that displays a total number of K f = 8 channels. As described above, Φ[k] (with k = 0, ..., K) f - 1) an unwrapped phase measurement for the respective channel k.

[0051] In the Fig. In the example shown, two [m, n]-channel pairs [0,7] and [1,6] are selected and the total phase difference ΔΦ is calculated. tot According to equation (22) the following is determined: ΔΦtot=Φ[7]−Φ[0]7+Φ[6]−Φ[1]52 including an associated deviation of the overall phase difference σΔΦtot=σ⋅(27)2+(25)22=σ⋅0.174

[0052] Therefore, the deviation of the total phase difference is scaled by 0.174, which is an improvement compared to using only a single outer pair: ΔΦs=Φ[7]−Φ[0]7→σΔΦs=σ⋅27=σ⋅0.202

[0053] A higher number of channel pairs will be considered in the following example. Example: Symmetrical pairing

[0054] Fig. 2 shows a diagram that shows a total number of K f = 8 channels with four pairs, where each pair combines two channels. It is noted that the in Fig. The selection shown is merely an example and other combinations of channel pairings can also be used.

[0055] Symmetrical pairing indices can be defined for any number of channels as follows: u=1,2,…,U where u is the pair index and U is the number of pairs used, max(U)=Kf2mu=u−1nu=Kf−u

[0056] The Canal Delta is the following: d[u]=Kf+1−2u

[0057] The resulting scaled phase difference of each pair with index u is: ΔΦs[mu,nu]=ΔΦs[u]=ϕ[nu]−ϕ[mu]Kf+1−2u

[0058] Therefore, K can be used for any number of channels. f Pairs are determined sequentially, starting from the edges and moving towards the center. The total phase difference at each point U is: ΔΦtot[U]=1U⋅∑u=1UΔΦs[u],U=1,…,Kf2

[0059] The term ΔΦ s [u] is the scaled phase difference defined in equation (20), U is the number of pairs added up to this point.

[0060] The deviation of the overall phase difference can be described as follows: ΔΦtot[U]=σ⋅∑u=1U(2Kf+1−2u)2U

[0061] This example demonstrates a significant improvement in accuracy compared to state-of-the-art solutions. The outer pairs with the largest delta between the channels exhibit the smallest deviations. Initially, each added pair reduces the overall deviation. However, due to the large deviation of the middle pairs, their addition eventually increases the overall deviation. Therefore, one option is to omit those middle pairs that contribute to the increased deviation (e.g., by comparing which pairs should (not) be omitted to a threshold value).

[0062] To further reduce the deviation, a weighted averaging of random variables can be used. Example: Improvement through weighted averaging

[0063] N1 and N2 are normal (e.g., random) distributions with standard deviations σ1 and σ2, respectively. The normal distributions N1 and N2 are uncorrelated, i.e., ρ(N1,N2)=0

[0064] Furthermore, it is assumed that N2 has a worse deviation by a factor of X, i.e. σ2=X⋅σ1,X>1.

[0065] The weighted mean M of two variables (here the normal distributions N1 and N2) is defined as follows: M=g1⋅N1+g2⋅N2g1+g2=1

[0066] The standard deviation σ M The mean value M can be determined as follows: σM=(g1σ1)2+(g2σ2)2==(g1σ1)2+((1−g1)⋅σ1⋅X)2==σ1⋅g12⋅(1+X2)−2g1X2+X2

[0067] A partial derivative with respect to the weight g1 is used to find the minimum standard deviation: ∂(g12⋅(1+X2)−2g1X2+X2)∂g1=2g1⋅(1+X2)−2X2

[0068] Then the weighting is determined, which results in a minimal standard deviation, i.e.: 2g1min⋅(1+X2)−2X2=0 g1min=X2X2+1

[0069] Next, this optimized weighting g will be 1min inserted back into equation (37) to find the minimum standard deviation, i.e.: σMmin=σ1⋅X2X2+1

[0070] Therefore, the optimal weights lead to the minimum deviation of the mean M and can be determined based on equation (40): g1=X2X2+1,g2=1−g1

[0071] Applying the optimal weights results in the minimum deviation of equation (41).

[0072] Therefore, a larger factor X leads to a reduced benefit from the second distribution N2. Example: Applying weights to symmetrical pairings

[0073] To obtain optimal weightings, the following iterative procedure of optimal weighted averaging can be used: a. Selecting a single pair as the first data point. Note that any pair can be selected. b. Subsequently adding the remaining pairs: The weights at each iteration can be calculated according to equation (42), where the normal distribution N1 corresponds to the full sum up to this point and N2 denotes the newly added pair of channels. c. The resulting optimal weight g[u] for each pair is calculated from the product of all weights applied to that pair over the entire iterative procedure. d. The sum of all g[u] weights should be 1.

[0074] Therefore, the overall phase difference is equal to a weighted average: ΔΦtot=∑u=1Ug[u]⋅ΔΦs[u] with ∑u=1Ug[u]=1

[0075] This approach has the advantage that the deviation is gradually reduced, with each channel pair being added with optimized weights.

[0076] It is noted that the example of symmetrical pairing is one of several approaches to obtain improved accuracy. Interim conclusion

[0077] The examples described herein lead to improved range determination accuracy compared to prior art solutions. For example, some embodiments for improving range determination accuracy may be based on one or more of the following: - Cumulative addition of phase differences to obtain the unwrapped phase for each channel - Equation (16). - Definition of the scaled phase difference according to equation (17). - Obtaining the range from a mean of several scaled phase differences according to equation (22).

[0078] Embodiments can further improve the range determination accuracy by using one or more of the following: - Selecting an arrangement of scaled phase differences. - Defining the weightings for each pair in a weighted averaging operation.

[0079] By preserving the unwrapped phases, each channel pair can be processed as a unique area measurement. The subsequent optimization steps, i.e., selecting the scaled phase differences and their weightings, can be performed in various ways. The selection itself can significantly impact the precision improvement. The solution described here can be used to achieve optimized precision.

[0080] The examples described herein can be used for Bluetooth high-precision distance measurement (HADM) or in any multi-carrier phase-difference rangefinder (MCPD rangefinder) as well as a step-frequency continuous wave radar (SFCW radar).

[0081] The solutions described herein can be implemented in hardware, firmware and / or software. Example: Pairing approach in systems with non-constant frequency channel delta

[0082] The examples above are based on the assumption that the frequency channels are spaced apart by a constant frequency difference Δω, as described in equation (5). In addition to this example, the spacing between frequency channels can be (at least partially) different. Therefore, the spacing between the channels in Fig. The two channels shown Φ[k] are not equidistant.

[0083] In such a case, symmetrical pairing can be used. Without the constant frequency difference Δω, the angular frequency for each channel is denoted as: ω[k]k=1,…,Kf

[0084] Thus, the scaled phase difference can be replaced by a phase-over-frequency term as follows: ΔϕΔω[m,n]=Φ[n]−Φ[m]ω[n]−ω[m]

[0085] For an example with K f The area is determined according to symmetrical pairing as follows: = 8 r=−c02⋅mean(ΔϕΔω[0.7], ΔϕΔω[1.6], ΔϕΔω[2.5], ΔϕΔω[3.4])

[0086] Furthermore, accuracy can be improved by using a weighted average according to: r=−c02⋅mean(g07⋅ΔϕΔω[0.7], g16⋅ΔϕΔω[1.6], g25⋅ΔϕΔω[2.5], g34 ⋅ΔϕΔω[3.4]) where optimized weightings (g 07 ,G 16 ,G 25 ,G 34) can be determined as shown in equation (3). Alternatively, the optimized weights can be derived iteratively, as also explained herein. Derivation of the optimized weighting equation with cross-correlation

[0087] Alternatively, the cross-correlation between random variables N1 and N2 can be ρ instead of 0, i.e. ρ(N1,N2)=ρ is applicable instead of equation (34).

[0088] The standard deviation σ M The mean value M can be determined as follows: σM=(g1σ1)2+(g2σ2)2+2ρ⋅(g1σ1)⋅(g2σ2)==(g1σ1)2+((1−g1)⋅(Xσ1)) 2+2ρ⋅(g1σ1)⋅((1−g1)⋅Xσ1)==σ1⋅g12⋅(1+X2−2ρX)+g1⋅(−2X2+2ρX)+X2

[0089] A partial derivative with respect to the weight g1 is used to find the minimum standard deviation: ∂(g12⋅(1+X2−2ρX)+g1⋅(−2X2+2ρX)+X2)∂g1==2g1⋅(1+X2−2ρX)−2X2+2ρX

[0090] Then the weighting is determined, which results in a minimal standard deviation, i.e.: 2g1min⋅(1+X2−2ρX)−2X2+2ρX=0 g1min=X2−ρXX2−2ρX+1

[0091] Next, this optimized weighting g will be 1min inserted back into equation (50) to find the minimum standard deviation, i.e.: σMmin=σ1X2⋅(1−ρ2)X2−2ρX+1 Example: Adjusting weights based on RSSI measurements

[0092] One problem with wireless communication is interference noise from other transmission systems operating within shared frequency ranges. This interference noise can reduce the signal-to-noise ratio (SNR) for a given channel, which then limits the range determination accuracy.

[0093] Signal and noise power levels can be determined, for example, estimated, based on a received signal strength indicator (RSSI). Signal power can then be determined based on RSSI measurements taken during range-finding transmissions. Furthermore, noise power can be determined based on RSSI measurements by sampling the received signal during transmission pauses. Such transmission pauses can be any of the following: pauses before range-finding sequences or pauses between channel changes within a range-finding sequence.

[0094] Channels with lower SNR can contribute to a higher standard deviation of the total phase difference. Therefore, to optimize the standard deviation of the total phase difference, the weights in equation (43) can be adjusted based on an SNR estimate provided by RSSI measurements.

[0095] For example, weights for channel pairs with a lower estimated SNR, determined based on RSSI measurements, can be reduced, whereas weights for channel pairs with a higher estimated SNR, determined based on RSSI measurements, can be increased.

[0096] The RSSI can be used to measure noise and / or signal power. Example: Brute-force mating

[0097] Brute-force pairing is directed at any combination of channel pairings used to improve accuracy.

[0098] The total number of unique channel pairings can be calculated using the binomial coefficient. (Kf2) will be calculated.

[0099] An example involves the total number of unique pairs arranged in a random, pseudorandom (or even deterministic), or arbitrary order. These can be added iteratively to gradually improve accuracy, as explained above in relation to symmetric pairing.

[0100] The iterative summation process can be adapted as follows: a. The brute-force pairing example uses overlapping pairs, which leads to cross-correlation between the pairs. Thus, the equations for the optimized weighted mean for uncorrelated variables in equation (42) can be replaced by the extended version according to equation (53). b. Furthermore, the use of overlapping channels can increase the complexity of the calculations. Therefore, framing the channel pairs and their corresponding weights into individual channels and corresponding factors can be advantageous. Additionally, during the iterative summation procedure, the factors of individual channels can be tracked instead of the weights of the corresponding channel pairs.

[0101] The factor applied to each individual channel is equal to the weighting of the respective channel pair, divided by the channel delta of that particular pair, including the correct sign: F[n]=+g[m,n]d[m,n]F[m]=−g[m,n]d[m,n]

[0102] Since factors of the same magnitude and opposite sign are preferentially added together, the total sum of factors applied to all channels is equal to 0, i.e., ∑k=0Kf−1F[k]=0

[0103] The optimized total phase difference given in equation (43) can thus be rewritten as: ΔΦtot=∑k=0Kf−1F[k]⋅Φ[k]

[0104] In this example of brute-force pairing, iteratively adding channel pairs in any order can be used to improve accuracy. Example: Equidistant mating

[0105] An equidistant pairing is defined by an equal distance d, which is used for each pair. d=const.nu=mu+d

[0106] The phase difference, defined by the individual pairs and their standard deviation, is: ΔΦs[mu,nu]=ΔΦs[u]=Φ[nu]−Φ[mu]d σΔΦs=σ⋅2d

[0107] The total phase difference and the deviation from the total phase difference are: ΔΦtot=1U⋅∑u=1UΔΦs[u] σΔΦtot=σ⋅2d⋅U where U is defined as the number of pairs used and u is the pair index.

[0108] Fig. Figure 3 shows a diagram that displays a total number of K f = 8 channels included. Different distances d are visualized for an example equidistant pairing. This is in Fig. 3 for d = 2 in a subdiagram 301, for d = 3 in a subdiagram 302, for d = 5 in a subdiagram 303 and for d = 6 in a subdiagram 304.

[0109] In all examples of Fig. In step 3, Φ[0] is used as a starting point and equidistant pairing with the respective distance d is applied until no more channel pairing is available. This results in some unused data points, i.e., Φ[4] to Φ[7] in subdiagram 301 or Φ[2] to Φ[5] in subdiagram 304.

[0110] The following applies: - for d <Kf2 The unused data points are located on the right-hand side, see sub-diagrams 301 and 302; and - for d>Kf2 The unused data points are located in the middle (i.e., between the data points), see sub-diagrams 303 and 304.

[0111] Therefore, the following applies - for d≤Kf2 the number of pairs used U = d, - for d>Kf2 the number of pairs used U = K f - d.

[0112] Therefore, the deviation according to equation (63) can be summarized as follows: σΔΦtot=σ⋅2d⋅d,fu¨rd≤Kf2 σΔΦtot=σ⋅2d⋅Kf−d,fu¨rd>Kf2

[0113] Advantageously, the distance d can be set to d=23⋅Kf can be set which, combined with equation (65), leads to an optimized deviation which is as follows: σΔΦtot=σ⋅13.5Kf3

[0114] In equidistant pairing, the same factor is applied to all pairs. This means that the number of multiplications can be reduced to a single multiplication, resulting in reduced implementation complexity. ⋅1d⋅U according to equation (62). Example: Extended equidistant mating

[0115] As stated above, equidistant matching can result in unused data points (also called residual data points). The number R of unused data points is: R=Kf−2⋅U

[0116] An extended equidistant matching approach is proposed, which utilizes the remaining data points by applying additional rounds of equidistant matching. This solution further reduces the standard deviation.

[0117] Fig. Figure 4 shows an example of an extended equidistant pairing based on the one in Fig. 3 shown in subdiagram 304. Here, the data points Φ[2] to Φ[5] are used in a second round of equidistant pairing.

[0118] Therefore, the following applies to the first round of equidistant pairing: Kf=8, d=6, U=2, R=4 as in subdiagram 304 of Fig. 3 shown. In the second round, or equidistant pairing, an extended pairing is realized, and the following applies (R of the first round equals K). f (of the second round): Kf=4, d=2, U=2, R=0. Advantageously, the distance can be used according to equation (66).

[0119] It is noted that the resulting phase difference ΔΦ of each step can lead to varying deviations. Therefore, a weighted average can be used to improve the result. Example: Equidistant pairing with binary powers

[0120] Multiplication or division by values ​​that are binary powers can be implemented as bit-shifting operations. This further reduces implementation costs.

[0121] The example of binary powers corresponds to the equidistant pairing scenario, where the distance d and the number of pairs used U are (reduced to) binary powers.

[0122] An advantageous deviation can be beneficial for Kf=d⋅32 as per equation (66). One implementation can select K f out of Kf=2K⋅32 Use positive integers K = 1, 2, 3, ...

[0123] Thus, the number of pairs used also leads to... U=Kf−d to a binary power, because U=2K⋅32−2K=2K⋅12=2K−1 Multipath processing

[0124] The pairing patterns (and optionally the weights) can be selected based on the amplitudes of IQ samples or values ​​(for details on in-phase and quadrature components, see, for example, https: / / en.wikipedia.org / wiki / In-phase_and_quadrature_components). One goal here could be multipath attenuation.

[0125] Multipath attenuation depends on the relative distance to a direct path. Multipaths with a larger relative distance can be easier to detect and attenuate than multipaths with a smaller distance. A distance difference Δr MP between the multipath distance r MP and the direct path distance r DP can be specified as ΔrMP=rMP−rDP

[0126] For example, Bluetooth has a minimum relative distance of 2π for a full amplitude period. r2π=cBW≈3⋅108ms80MHz=3.75m where BW is the bandwidth and c is the speed of light.

[0127] According to an exemplary embodiment, three multipath (MP) categories can be defined:

[0128] First, a FAR-MP category that spans at least two peaks or at least two troughs of the amplitude signal of IQ samples. This results in a spacing difference Δr. MP , which is as follows: ΔrMP≥r2π

[0129] Secondly, a MID-MP category is defined, which includes one peak and one trough of the amplitude signal of the IQ samples. This results in a spacing difference Δr. MP , which is as follows: r2π2<ΔrMP <r2π

[0130] Third, a NEAR-MP category is defined, which includes either 1 peak (and no trough) or 1 trough (and no peak) of the amplitude signal of the IQ samples. This results in a distance difference Δr. MP, which is as follows: ΔrMP≤r2π2

[0131] It is noted that the following assumptions can preferably be made for the examples described herein: There is a single dominant multipath. The performance of the multipath is lower than the performance of the direct path. A peak-search algorithm is applied to the amplitude of the IQ samples to identify peaks and troughs.

[0132] Fig. Figure 5 shows a diagram illustrating the FAR-MP category, which uses equidistant peak-to-peak (or valley-to-valley) pairing.

[0133] An amplitude 501 of the IQ samples is plotted across the channels. The y-axis for the amplitude is on the right side of the graph. The y-axis on the left side of the graph shows the values ​​for the phases. An ideal phase 502 and a phase 503, encompassing the direct path and the multi-path, are shown. The pairing can be performed as follows: a. Take an amplitude at point 511. Determine the channel k = 8 for this point 511. b. Determine the associated phase Φ[8] based on curve 503. c. The pairing distance is determined as a distance 504 between two peaks, resulting in a peak amplitude at point 512. The associated channel for point 512 results in l = 48. d. Determine the associated phase Φ

[48] based on curve 503.

[0134] Thus, the pairing includes the phase values ​​Φ[k] and Φ[l]. The next pair is based on the channels k + 1 and l + 1. The pairing can be continued with additional values ​​i > 1 until k + l is reached. In this example, due to the distance 504, the difference between k and l is 40. Thus, for example, phase values ​​Φ[k = 24] and Φ[l = 64] can be paired, as shown by arrow 505. It is evident that the differences between curve 503 and the ideal phase 502 are identical at k = 24 and l = 64.

[0135] Determining the phase difference ΔΦ between the paired phases, the multipath bias within each pair is calculated based on ΔΦ=Φ[l]−Φ[k] lifted.

[0136] Fig. Figure 6 shows a diagram illustrating the MID-MP category, which uses equidistant peak-to-trough pairing.

[0137] An amplitude of 601 IQ samples is plotted across the channels. The y-axis for amplitude is on the right side of the graph. The y-axis on the left side of the graph shows the phase values. An ideal phase of 602 and a phase of 603, encompassing the direct path and the multi-path, are shown. The pairing can be performed as follows: a. Take an amplitude at point 611. Determine the channel k = 16 for this point 611. b. Determine the associated phase Φ

[16] based on curve 603. c. The mating distance is determined as the distance 604 between the peak and the trough, resulting in an amplitude at point 612. The associated channel for point 612 is l = 55. d. Determine the associated phase Φ

[55] based on curve 603.

[0138] Thus, the pairing includes the phase values ​​Φ[k] and Φ[l]. The next pair is based on the channels k + 1 and l + 1. The pairing can be continued with additional values ​​i > 1 until k + il is reached.

[0139] In this example, due to the distance of 604, the difference between k and l is 39. However, the multipath error within the pair is not canceled. Instead, the multipath error can be canceled by summing two pairs with opposite multipath-induced preloads.

[0140] In relation to Fig. 6. The following example applies with regard to pairing (the numbers in parentheses indicate the channels): - [39, 0], see arrow 621, which leads to ΔΦ1 = Φ

[39] - Φ[0] - [71, 32], see arrow 622, which leads to ΔΦ2 = Φ

[71] - Φ

[32] .

[0141] Here, the multipath error can be canceled by summing ΔΦ1 and ΔΦ2. The opposite multipath-induced prestresses, i.e., Φ[0] and Φ

[32] , can be found such that they are arranged symmetrically around the intersection point between lines 602 and 603.

[0142] It is noted that this approach can also be applied to the FAR-MP category, which has more than one peak and trough.

[0143] In the NEAR-MP category, a combination of peak and trough does not fall within the window to be considered. Instead, there is either only a peak or only a trough. Two approaches to reduce multipath-induced bias are presented below.

[0144] Assuming that the multipath bias contributes to a region error, a bias determined based on the amplitude deviation can be used to reduce the error.

[0145] Fig. Figure 7 shows a diagram illustrating the NEAR-MP category, which includes an amplitude of 701 IQ samples across the channels. The y-axis for amplitude is on the right side of the diagram. The y-axis on the left side of the diagram shows the phase values. An ideal phase of 702 and a phase of 703, encompassing the direct path and multipath respectively, are shown.

[0146] Since the multipath error contributing to phase 703 always adds some distance that is not in the direct path, a negative bias based on the amplitude deviation can be applied to improve the result. For example, if the deviation increases, the bias can also be increased.

[0147] As an alternative to addressing the NEAR-MP category, the range of mating patterns can be limited: Fig. Figure 8 shows a diagram illustrating the NEAR-MP category with a limited range for the pairing patterns. An amplitude 801 shows the amplitude of the IQ sample values ​​across the channels. The y-axis for amplitude is on the right side of the diagram. The y-axis on the left side of the diagram shows the values ​​for the phases. An ideal phase 802 and a phase 803, which include the direct path and the multipath, are shown.

[0148] The pairing patterns can be limited to a region 804, e.g., around a peak 805 of the amplitude 801 of the IQ sampling values. It is noted that the region could also be applied around a trough (instead of the peak). This solution has the advantage that the pairing patterns used within the region 804 are directed towards the phase 803 with the smallest deviation (compared to the deviation from the ideal phase 802 outside the region 804). Additional aspects and designs

[0149] Fig. Figure 9 illustrates an exemplary flowchart of a Method 900 for operating a device for performing range measurements. The Method 900 can be carried out by a device using hardware, software, or combinations of hardware and software.

[0150] In Operation 901, several phase differences are determined, with each phase difference being based on a pair of phase measurements.

[0151] Operation 902 calculates an overall phase difference based on multiple phase differences. Each phase difference is also weighted.

[0152] In Operation 903, the area is determined based on the total phase difference.

[0153] It is noted that it is an option for the weights to be equal for at least two of the phase differences. In particular, it is an option for the weights to be equal for all phase differences. Such an example leads to equidistant pairing. In a specific example of equidistant pairing, the weights for the phase differences can be set to 1.

[0154] As an option, determining the total phase difference in Operation 902 can include: reducing or minimizing a deviation for each of the phase differences or for a selection of phase differences.

[0155] As a further option, determining the multiple phase differences according to Operation 901 may also include: reducing or minimizing the deviation by selecting pairs of phase measurements and / or by adjusting the weights for the phase differences.

[0156] Fig. Figure 10 shows an example block diagram that visualizes different use cases for a system implementation. An initiator 1001 transmits a wireless signal to a reflector 1002 and / or to an object in the environment 1003. The initiator 1001 and the reflector can be implemented as transceiver devices. The reflector 1002 and the object in the environment 1003 can reflect part of the wireless signal back to the initiator 1001.

[0157] The examples described herein can be applied to range measurements between two transceivers, in this example between the initiator 1001 and the reflector 1002, also known as transceiver-to-transceiver range determination. Alternatively (or additionally), a range measurement can be applied between the initiator 1001 and the surrounding object 1003, also known as transceiver-to-object range determination.

[0158] Transceiver-to-transceiver range determination can be performed, for example, for localization, navigation, and / or secure access purposes. The initiator 1001 initiates the range measurement, and the reflector 1002 responds to this initiation. Exemplary use cases for transceiver-to-transceiver range determination can include, without limitation, the following: A smartphone is used as the initiator to locate a wireless headphone (e.g., earbuds) or another wireless element (e.g., a tracking device attached to a keyring). In this example, the wireless headphone and the wireless element are transceiver devices used as reflectors. A smartphone or other wireless device is used to unlock a door, such as a car door or a smart lock. The smartphone / wireless device can be the initiator, and the car door / smart lock can be used as a reflector. A beacon tracks a smartphone or smartwatch, for example, during a user's indoor movement. This example can be used for indoor sports or indoor navigation. The smartphone / smartwatch can act as either an initiator or a reflector. Therefore, the beacon assumes the opposite role, i.e., reflector or initiator. A smartphone or smartwatch is used for secure payment. The smartphone / smartwatch can act as either the initiator or the reflector. Therefore, the other party, in this case the payment device, assumes the opposite role, i.e., reflector or initiator.

[0159] Transceiver-to-object rangefinding solutions can also include radar applications that perform range measurement and / or object detection. Examples of transceiver-to-object rangefinding solutions can include, without limitation: A computer logs out when a user moves away from it. Here, the object is the user who is (no longer) detected by the computer. Accordingly, a login procedure can be started when a user is detected in front of the computer. - A beacon determines and / or tracks the presence of a person and performs a predefined action, e.g., turning lights on / off, turning air conditioning on / off, adjusting a lighting level, adjusting an air conditioner. A radar device can be used to detect objects that are not visible to the human eye. For example, objects that are underground or behind barriers can be detected by radar signals.

[0160] The wireless signal addressed herein may include at least one of the following: a wireless fidelity signal (WiFi signal), a Bluetooth signal (BT signal), or an ultra-wideband signal (UWB signal).

[0161] Fig.Figure 11 illustrates a block diagram of a system 1100 that can be used for range measurement. In this embodiment, a wireless device 1101 acts as a central device (CD) of the wireless network and can be referred to herein as a receiving device. Furthermore, a wireless device 1170 acts as a peripheral device (PD) of the wireless network and can be referred to herein as a transmitting device. The system 1100 can include a secured resource 1150, which is secured, for example, by means of a locking mechanism 1160, wherein the peripheral wireless device 1170 is designed to gain access to the secured resource 1150 via the locking mechanism 1160. The secured resource 1150 can be, for example, an enclosure such as a vehicle, a building, a residence, a garage, a shed, a safe, or the like.The secured resource 1150 can also be a computer system, industrial equipment, or other items that require secure access via the locking mechanism 1160, which can be, for example, a digital locking mechanism. In some embodiments, the locking mechanism 1160 can be integrated together with the central wireless device 1101.

[0162] In some embodiments, the peripheral wireless device 1170 is any one of several peripheral wireless devices, since the central wireless device 1101 can be configured to communicate with any or all of such peripheral wireless devices. In some embodiments, the peripheral wireless device 1170 is a mobile device such as a mobile phone, smartphone, smartwatch, pager, electronic transceiver, tablet, keyless entry device, or the like. In these embodiments, the peripheral wireless device 1170 can be configured to gain access to the secured resource 1150 by transmitting data, including a frame synchronization pattern (e.g., a BLE channel probing synchronization pattern (BLE-CS synchronization pattern)) encapsulated in a frame synchronization packet.The peripheral wireless device 1170 may also include the same or similar components as the central wireless device 1101, the descriptions of which are not repeated here for the sake of brevity.

[0163] In some embodiments, the central wireless device 1101 includes, among other things, a transmitter or TX 1102 (e.g., a PAN transmitter), a receiver or RX 1104 (e.g., a PAN receiver), a communication interface 1106, one or more antennas 1110, a memory 1105, one or more input / output devices (I / O devices) 1108 (such as a display screen, a touchscreen, a keyboard, and the like), and a processor 1120. These components can all be coupled to a communication bus 1130.

[0164] In some embodiments, a separate antenna can be used for each of the transmitter 1102 and / or the receiver 1104, so that antenna 1110 is illustrated for simplicity. In some embodiments, the memory 1105 can include memory for storing instructions executable by the processor 1120 and / or data generated by the communication interface 1106. In some embodiments, front-end components such as the transmitter 1102, the receiver 1104, the communication interface 1106, and the one or more antennas 1110 described herein can be designed or configured with PAN-based frequency bands, e.g., Bluetooth® (BT), BLE, Wi-Fi®, Zigbee®, Z-wave™, and the like.

[0165] In some embodiments, the communication interface 1106 is integrated with the transmitter 1102 and the receiver 1104, e.g., as the front end of the wireless device 1101. The communication interface 1106 can coordinate, as instructed by the processor 1120, requesting / receiving packets from the peripheral wireless device 1170. The communication interface 1106 can process data symbols received by the receiver 1104 in such a way that the processor 1120 can perform further processing as described herein.

[0166] Different embodiments of the range determination measurement described herein may include different operations. These operations may be performed and / or controlled by hardware components, digital hardware and / or firmware / programmable registers (e.g., as implemented in a computer-readable medium), and / or combinations thereof. For example, the operations may be performed by a general-purpose computer or a processing system executing a computer program stored in a computer-readable medium. The methods and illustrative examples described herein do not inherently refer to any particular device or other facility. Various systems (e.g., a wireless device operating in a near- or far-range environment, a pico-range network, a wide-range network, etc.) are possible.) can be used in accordance with the teachings described herein, or it may prove useful to construct a more specialized facility to carry out the procedural steps.

[0167] A computer-readable medium used to implement operations of various aspects of the revelation may be, but is not limited to, a non-volatile computer-readable storage medium, which may include an electromagnetic storage medium, a magneto-optical storage medium, a read-only memory (ROM), a random-access memory (RAM), a erasable programmable memory (e.g., EPROM and EEPROM), a flash memory, or any other non-volatile type of medium, now known or subsequently developed, suitable for storing configuration information.

[0168] The foregoing description is intended to be illustrative and not limiting. Although the present disclosure has been described with reference to specific illustrative examples, it is understood that the present disclosure is not limited to the examples described. The scope of the disclosure should be determined with reference to the following claims together with the full scope of equivalents to which the claims entitle the holder.

[0169] As used herein, the singular forms "a," "an," and "the" are to be understood as including the plural forms unless the context clearly indicates otherwise. It is further understood that the terms "includes," "including," "may include," and / or "containing," when used herein, indicate the presence of specified features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. Therefore, the terminology used herein serves only to describe certain embodiments and is not intended to be restrictive.

[0170] It should also be noted that in some alternative implementations, the noted functions / steps may occur out of the order shown in the figures. For example, two figures shown consecutively may actually be executed essentially simultaneously, or may sometimes be executed in reverse order, depending on the functionality / steps involved.

[0171] Although the procedural operations have been described in a specific sequence, it is understood that other operations can be performed between the described operations, that the described operations can be adapted to occur at slightly different times, or that the described operations can be distributed in a system that allows the processing operations to occur at various intervals associated with the processing. For example, certain operations can be performed, at least partially, in reverse order, simultaneously, and / or in parallel with other operations.

[0172] Various units, circuits, or other components may be described or claimed to be "configured to" or "configurable to" perform a task or tasks. In such contexts, the expression "configured to" or "configurable to" is used to denote a structure by indicating that the units / circuits / components contain a structure (e.g., a circuit) that performs the task or tasks during operation. Thus, it can be said that the unit / circuit / component is configured to perform the task, or is configurable to perform the task, even if the specified unit / circuit / component is not currently operational (e.g., not powered on).The units / circuits / components used with the language "configured to" or "configurable to" include hardware—for example, circuits, memory that stores program instructions executable to implement the operation, etc. The statement that a unit / circuit / component is "configured to" perform one or more tasks or "configurable to" perform one or more tasks is expressly not intended to invoke 35 USC 112, sixth paragraph, for that unit / circuit / component.

[0173] Additionally, "configured to" or "configurable to" can include a generic structure (e.g., a generic circuit) that is manipulated by firmware (e.g., an FPGA) to operate in a way capable of performing the task(s) in question. "Configured to" can also include adapting a manufacturing process (e.g., a semiconductor manufacturing facility) to produce devices (e.g., integrated circuits) adapted to implement or perform one or more tasks. i“Configurable to” is expressly not to be applied to blank media, an unprogrammed processor or an unprogrammed programmable logic device, a programmable gate arrangement or any other unprogrammed device unless accompanied by programmed media that enable the unprogrammed device to be configured to perform the disclosed function(s).

[0174] The foregoing description has been provided for illustrative purposes with reference to specific embodiments. However, the foregoing illustrative discussions are not intended to be exhaustive or to limit the claimed subject matter to the exact forms disclosed. In light of the foregoing teachings, many modifications and variations are possible. The embodiments have been chosen and described to explain the principles of the embodiments and their practical applications, thereby enabling other skilled persons to use the embodiments and various modifications as they may be suitable for the particular use under consideration.Accordingly, the present embodiments are to be regarded as illustrative and not limiting, and the claimed subject matter is not to be limited to the details given herein, but may be modified within the scope and equivalents of the attached claims. Other exemplary embodiments:

[0175] The examples proposed herein may be based on at least one of the following solutions. Combinations of the following features could be used to achieve a desired result. The features of the method could be combined with any feature(s) of the device, apparatus, or system, or vice versa. The “embodiments” mentioned herein are merely examples of features that could optionally be introduced. These embodiments do not limit the independent claims.

[0176] A method for phase-based range measurement is proposed, including: Determining a multitude of phase differences, each of which is based on a pair of phase measurements; Determining an overall phase difference based on the plurality of phase differences, where each of the plurality of phase differences is weighted; and Determining a range based on the total phase difference.

[0177] It is noted that it is an option for the weights to be equal for at least two of the phase differences. In particular, it is an option for the weights to be equal for all phase differences. Such an example leads to equidistant pairing. In a specific example of equidistant pairing, the weights for the phase differences can be set to 1.

[0178] According to one embodiment, determining the total phase difference involves reducing or minimizing a deviation for each of the plurality of phase differences or for a selection of the plurality of phase differences.

[0179] According to one embodiment, determining the total phase difference further includes reducing or minimizing the deviation by selecting pairs of phase measurements and / or by adjusting the weights for the multitude of phase differences.

[0180] According to one embodiment, determining the plurality of phase differences further includes selecting pairs of phase measurements, wherein the pairs are arranged symmetrically over frequency channels.

[0181] According to one embodiment, the multitude of phase differences is determined by pairs of phase measurements, wherein the pairs are arranged equidistantly across frequency channels.

[0182] According to one embodiment, the multitude of phase differences is determined by pairs of phase measurements, wherein the pairs are arranged equidistantly across the frequency channels, with at least two groups of pairs being provided with different spacings, wherein at least one group includes at least two pairs.

[0183] According to one embodiment, determining the plurality of phase differences includes at least one of selecting pairs of phase measurements with a distance that is a power of 2, and selecting a number of pairs of phase measurements, wherein this number is a power of 2.

[0184] According to one embodiment, determining the multitude of phase differences involves selecting pairs of phase measurements based on an amplitude of IQ values ​​and / or based on an amplitude of RSSI measurements.

[0185] According to one embodiment, determining the weighting of each of the multitude of phase differences is based on the amplitude of the IQ values ​​and / or the RSSI measurements.

[0186] Furthermore, an exemplary setup is proposed, including: a receiver configured to receive radio frequency (RF) signals associated with a variety of phase values; a processing system configured to: Determining a multitude of phase differences, each phase difference being based on a pair of phase measurements; Determining an overall phase difference based on the multitude of phase differences, where each of the phase differences is weighted; and Determining a range of a source of at least a portion of the RF signals based on the total phase difference.

[0187] According to one embodiment, in order to determine the total phase difference, the processing system is configured to reduce or minimize a deviation for each of the phase differences or for a selection of the phase differences.

[0188] According to one embodiment, to determine the total phase difference, the processing system is configured to reduce or minimize the deviation by selecting pairs of phase measurements and / or by adjusting the weights for the phase differences.

[0189] According to one embodiment, to determine the multitude of phase differences, the processing system is configured to select pairs of phase measurements, the pairs being arranged symmetrically across frequency channels.

[0190] According to one embodiment, the processing system is configured to determine the multitude of phase differences by pairs of phase measurements, wherein the pairs are arranged equidistantly across frequency channels.

[0191] According to one embodiment, the processing system is configured to determine the multitude of phase differences by pairs of phase measurements, wherein the pairs are arranged equidistantly across the frequency channels, with at least two groups of pairs being provided with different spacings, wherein at least one group includes at least two pairs.

[0192] According to one embodiment, the processing system is configured as follows to determine the multiple phase differences: Selecting pairs of phase measurements with a separation that is a power of 2; and Selecting a number of pairs of phase measurements, where this number is a power of 2.

[0193] According to one embodiment, to determine the multiple phase differences, the processing system is configured to: select pairs of phase measurements based on an amplitude of IQ values ​​and / or based on an amplitude of RSSI measurements.

[0194] According to one embodiment, the processing system is configured to determine the weighting of each phase difference based on the amplitude of the IQ values ​​and / or the RSSI measurements.

[0195] Furthermore, an exemplary system is provided, including: an initiating device, including a transceiver; and a reflector device, wherein the initiating device is configured to receive wireless signals from the reflector device and, based on the wireless signals: Determining multiple phase differences, where each phase difference is based on a pair of phase measurements, Determining an overall phase difference based on the multiple phase differences, where each of the phase differences is weighted, Determining a range based on the total phase difference, and Initiating an action based on the specified area.

[0196] According to one embodiment, the reflector device is one of the following: a reflector device including a transceiver that transmits the wireless signals; or an object that provides wireless information via one or more physical reflections of radio waves.

[0197] An exemplary solution may be based on a computer program product that can be directly loaded into the memory of a digital computer, including sections of software code to perform the steps of the procedure as described herein.

[0198] Additionally, the problem stated above can be solved by a computer-readable medium, e.g., a memory of any kind, which contains computer-executable instructions adapted to cause a computer system to perform the procedure as described herein.

[0199] Furthermore, the problem stated above is solved by a communication system that includes at least one device or apparatus as described herein. QUOTES INCLUDED IN THE DESCRIPTION

[0000] This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited patent literature

[0000] US 9,274,218 B2

[0005] Cited non-patent literature

[0000] P. Zand, J. Romme, J. Govers, F. Pasveer and G. Dolmans, "A high-accuracy phase-based ranging solution with Bluetooth Low Energy (BLE)," 2019 IEEE Wireless Communications and Networking Conference (WCNC), 2019, pp. 1-8, doi: 10.1109 / WCNC.2019.8885791 [0002, 0008, 0015, 0020] Handbook of Mathematics, 6th Edition

[2015] - IN Bronshtein , KA Semendyayev, Gerhard Musiol, Heiner Mühlig, page 854

[0047]

Claims

[1] A method for phase-based range measurement, comprising: Determining a multitude of phase differences, each of which is based on a pair of phase measurements; Determining an overall phase difference based on the plurality of phase differences, where each of the plurality of phase differences is weighted; and Determining a range based on the total phase difference. [2] Method according to claim 1, wherein determining the overall phase difference includes reducing or minimizing a deviation for each of the plurality of phase differences or for a selection of the plurality of phase differences. [3] Method according to claim 2, wherein determining the total phase difference further includes reducing or minimizing the deviation by selecting pairs of phase measurements and / or by adjusting the weights for the plurality of phase differences. [4] Method according to claim 1, wherein determining the plurality of phase differences further includes selecting pairs of phase measurements, wherein the pairs are arranged symmetrically over frequency channels. [5] Method according to claim 1, wherein the plurality of phase differences is determined by pairs of phase measurements, the pairs being arranged equidistantly across frequency channels. [6] Method according to claim 5, wherein the plurality of phase differences is determined by pairs of phase measurements, wherein the pairs are arranged equidistantly across the frequency channels, wherein at least two groups of pairs with different spacings are provided, wherein at least one group includes at least two pairs. [7] Method according to claim 5, wherein determining the plurality of phase differences comprises at least one of selecting pairs of phase measurements with a distance that is a power of 2 and selecting a number of pairs of phase measurements, wherein this number is a power of 2. [8] Method according to claim 1, wherein determining the plurality of phase differences includes selecting pairs of phase measurements based on an amplitude of IQ values ​​and / or based on an amplitude of RSSI measurements. [9] Method according to claim 8, wherein determining the weighting of each of the plurality of phase differences is based on the amplitude of the IQ scores and / or the RSSI measurements. [10] An institution comprising: a receiver configured to receive radio frequency (RF) signals associated with a variety of phase values; a processing system configured to: Determining a multitude of phase differences, each phase difference being based on a pair of phase measurements; Determining an overall phase difference based on the multitude of phase differences, where each of the phase differences is weighted; and Determining a range of a source of at least a portion of the RF signals based on the total phase difference. [11] Device according to claim 10, wherein, for determining the overall phase difference, the processing system is configured to reduce or minimize a deviation for each of the phase differences or for a selection of the phase differences. [12] Device according to claim 11, wherein, for determining the total phase difference, the processing system is configured to reduce or minimize the deviation by selecting pairs of phase measurements and / or by adjusting the weights for the phase differences. [13] Device according to claim 10, wherein to determine the plurality of phase differences the processing system is configured to select pairs of phase measurements, the pairs being arranged symmetrically over frequency channels. [14] Device according to claim 10, wherein the processing system is configured to determine the plurality of phase differences by pairs of phase measurements, wherein the pairs are arranged equidistantly across frequency channels. [15] Device according to claim 14, wherein the processing system is configured to determine the plurality of phase differences by pairs of phase measurements, wherein the pairs are arranged equidistantly across the frequency channels, wherein at least two groups of pairs with different spacings are provided, wherein at least one group includes at least two pairs. [16] Device according to claim 10, wherein the processing system is configured to determine the plurality of phase differences as follows: Selecting pairs of phase measurements with a separation that is a power of 2; and Selecting a number of pairs of phase measurements, where this number is a power of 2. [17] Device according to claim 10, wherein the processing system is configured to determine the plurality of phase differences as follows: Selecting pairs of phase measurements based on an amplitude of IQ values ​​and / or based on an amplitude of RSSI measurements. [18] Device according to claim 17, wherein the processing system is configured for the following: Determining the weighting of each phase difference based on the amplitude of the IQ scores and / or the RSSI measurements. [19] A system comprising: an initiating device, including a transceiver; and a reflector device, wherein the initiating device is configured to receive wireless signals from the reflector device and, based on the wireless signals: Determining multiple phase differences, where each phase difference is based on a pair of phase measurements, Determining an overall phase difference based on the multiple phase differences, where each of the phase differences is weighted, Determining a range based on the total phase difference, and Initiating an action based on the specified area. [20] System according to claim 19, wherein the reflector device is one of the following: a reflector device including a transceiver that transmits the wireless signals; or An object that provides wireless signals via one or more physical reflections of radio waves.

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